We describe carbazolyl dicyanobenzene (CDCB)-based donor–acceptor (D–A) fluorophores as a class of cheap, easily accessible, and efficient metal-free photoredox catalysts for organic synthesis. By ...changing the number and position of carbazolyl and cyano groups on the center benzene ring, CDCBs with a wide range of photoredox potentials are obtained to effectively drive the energetically demanding C(sp3)–C(sp2) cross-coupling of carboxylic acids and alkyltrifluoroborates with aryl halides via a photoredox/Ni dual catalysis mechanism. This work validates the utility of D–A fluorophores in guiding the rational design of metal-free photoredox catalysts for visible-light-promoted organic synthesis.
Motivated by the LHCb's new observation of structures in the J/ψ-pair invariant mass spectrum, which could be classified as possible cccc tetraquark candidates, we systematically study 0+ ...fully-charmed tetraquark states through QCD sum rules. Developing the calculation techniques to fourfold heavy hadronic systems, four different configuration currents with 0+ are considered, and vacuum condensates up to dimension six are included in the operator product expansion. Finally, the mass values acquired for 0+ cccc tetraquark states agree well with the experimental data of the broad structure, which support that it could be a 0+ fully-charmed tetraquark state.
One prominent goal of 21st century research is to develop a sustainable carbon‐neutral biorefinery. Lignin is an important component of lignocellulosic biomass; however, it is currently underutilized ...owing to its highly cross‐linked, complex, and randomly polymerized composition, which poses a significant challenge to its depolymerization and valorization. Chemical catalytic approaches based on transition metals represent the primary research area to drive degradation reactions. Recently, alternative photocatalytic strategies that employ sustainable solar energy to initiate the transformation of lignin have started to emerge. This Concept article examines new developments of photocatalyzed reactions and provides insight into C−O and C−C bond‐cleavage reactions of lignin models in both homogeneous and heterogeneous systems.
Bring to light: Lignin is an important component of lignocellulosic biomass but is underutilized. This article examines the development of photocatalyzed reactions and provides insight into C−O and C−C bond‐cleavage reactions of lignin models in both homogeneous and heterogeneous systems. The opportunities and challenges of the ultimate photoredox catalytic conversion of lignin into value‐added commodity and fine chemicals are outlined.
Motivated by the LHCb's very recent observation of exotic X0(2900) in the B+ → D+D−K+ process, for which could be a good open-charm ud¯c¯s tetraquark candidate, we endeavor to investigate its ...possibility by means of QCD sum rules. In technique, four configurations of interpolating currents with JP = 0+ are studied for the ud¯c¯s tetraquark state. In the end, mass values are calculated to be ... GeV for the axial vector diquark-axial vector antidiquark configuration and ... GeV for the scalar diquark-scalar antidiquark configuration, both of which are consistent with the experimental data 2.866 ± 0.007 ± 0.002 GeV of X0(2900) in view of the uncertainty. These results support that X0(2900) could be a 0+ tetraquark state with open-charm flavor.
The overarching goal of this study was to look into the effects of academic self-efficacy and academic motivation on student long-term engagement and academic achievement. This study also sought to ...investigate the role of learning agility as a mediator in the relationship between academic self-efficacy and academic motivation. This study examined the impact of student sustainable engagement on student academic achievement as part of our model. A questionnaire technique was used to collect data from 325 music education students studying at various music training institutions in China. The data were analyzed using the Smart-PLS software and a structural equation modeling (SEM) technique. Academic self-efficacy and academic motivation were found to have a positive and significant relationship with student long-term engagement. The academic motivation was also found to have a positive relationship with student long-term engagement. Furthermore, learning agility was found to mediate the relationship between academic self-efficacy and student sustainable engagement. Furthermore, learning agility mediated the relationship between academic motivation and long-term student engagement. Furthermore, student sustainable engagement has a significant and positive relationship with student academic achievement. This paper made a valuable theoretical contribution by investigating the impact of academic self-efficacy and academic motivation on student sustainable engagement, as well as the impact of student sustainable engagement on student academic achievement. Furthermore, this study added to the body of knowledge by investigating the relationship through the lens of cognitive learning theory. In terms of practical implications, this paper would undoubtedly assist educational institutions in maintaining a fair and just learning environment that encourages students to be engaged and perform well. Future research can include other constructs to gain a better understanding of the factors that influence students’ academic engagement and achievement.
In the present paper, we investigate the dark energy equation of state using the Gaussian processes analysis method, without confining a particular parametrization. The reconstruction is carried out ...by adopting the background data including supernova and Hubble parameter, and perturbation data from the growth rate. It suggests that the background and perturbation data both present a hint of dynamical dark energy. However, the perturbation data have a more promising potential to distinguish non-evolution dark energy including the cosmological constant model. We also test the influence of some parameters on the reconstruction. We find that the matter density parameter
Ω
m
0
has a slight effect on the background data reconstruction, but has a notable influence on the perturbation data reconstruction. While the Hubble constant presents a significant influence on the reconstruction from background data.
Heteroatom‐doping is a promising strategy to tuning the microstructure of carbon material toward improved electrochemical storage performance. However, it is a big challenge to control the doping ...sites for heteroatom‐doping and the rational design of doping is urgently needed. Herein, S doping sites and the influence of interlayer spacing for two kinds of hard carbon, perfect structure and vacancy defect structure, are explored by the first‐principles method. S prefers doping in the interlayer for the former with interlayer distance of 3.997 Å, while S is doped on the carbon layer for the latter with interlayer distance of 3.695 Å. More importantly, one step molten salts method is developed as a universal synthetic strategy to fabricate hard carbon with tunable microstructure. It is demonstrated by the experimental results that S‐doping hard carbon with fewer pores exhibits a larger interlayer spacing than that of porous carbon, agreeing well with the theoretical prediction. Furthermore, the S‐doping carbon with larger interlayer distance and fewer pores exhibits remarkably large reversible capacity, excellent rate performance, and long‐term cycling stability for Na‐ion storage. A stable and reversible capacity of ≈200 mAh g−1 is steadily kept even after 4000 cycles at 1 A g−1.
Two kinds of S‐doped hard carbon with different microsctructures are synthesized by a universal synthetic strategy. It is demonstrated that S‐doping hard carbon with fewer pores exhibits a larger interlayer spacing than that of porous carbon, and an excellent Na‐ion storage performance with a stable capacity of ≈200 mAh g−1 after 4000 cycles at 1 A g−1 is displayed.
Aqueous Zn–iodine (Zn–I2) batteries have been regarded as a promising energy‐storage system owing to their high energy/power density, safety, and cost‐effectiveness. However, the polyiodide shuttling ...results in serious active mass loss and Zn corrosion, which limits the cycling life of Zn–I2 batteries. Inspired by the chromogenic reaction between starch and iodine, a structure confinement strategy is proposed to suppress polyiodide shuttling in Zn–I2 batteries by hiring starch, due to its unique double‐helix structure. In situ Raman spectroscopy demonstrates an I5−‐dominated I−/I2 conversion mechanism when using starch. The I5− presents a much stronger bonding with starch than I3−, inhibiting the polyiodide shuttling in Zn–I2 batteries, which is confirmed by in situ ultraviolet–visible spectra. Consequently, a highly reversible Zn–I2 battery with high Coulombic efficiency (≈100% at 0.2 A g−1) and ultralong cycling stability (>50 000 cycles) is realized. Simultaneously, the Zn corrosion triggered by polyiodide is effectively inhibited owing to the desirable shuttling‐suppression by the starch, as evidenced by X‐ray photoelectron spectroscopy analysis. This work provides a new understanding of the failure mechanism of Zn–I2 batteries and proposes a cheap but effective strategy to realize high‐cyclability Zn–I2 batteries.
Inspired by the significant chromogenic reaction between starch and iodine, the shuttle effect of Zn–I2 batteries is effectively addressed by using starch, which strongly anchors polyiodide anions due to its unique double‐helix structure. Benefiting from this structure confinement, a Coulombic efficiency of almost 100% and an ultralong life of 50 000 cycles are realized in Zn–I2 batteries.
With the aim of developing a fast yet accurate algorithm for compressive sensing (CS) reconstruction of natural images, we combine in this paper the merits of two existing categories of CS methods: ...the structure insights of traditional optimization-based methods and the speed of recent network-based ones. Specifically, we propose a novel structured deep network, dubbed ISTA-Net, which is inspired by the Iterative Shrinkage-Thresholding Algorithm (ISTA) for optimizing a general norm CS reconstruction model. To cast ISTA into deep network form, we develop an effective strategy to solve the proximal mapping associated with the sparsity-inducing regularizer using nonlinear transforms. All the parameters in ISTA-Net (e.g. nonlinear transforms, shrinkage thresholds, step sizes, etc.) are learned end-to-end, rather than being hand-crafted. Moreover, considering that the residuals of natural images are more compressible, an enhanced version of ISTA-Net in the residual domain, dubbed ISTA-Net+, is derived to further improve CS reconstruction. Extensive CS experiments demonstrate that the proposed ISTA-Nets outperform existing state-of-the-art optimization-based and network-based CS methods by large margins, while maintaining fast computational speed. Our source codes are available: http://jianzhang.tech/projects/ISTA-Net.
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