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"Zhou, Zhi"
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Electrically regulating nonlinear optical limiting of metal-organic framework film
Regulating nonlinear optical (NLO) property of metal−organic frameworks (MOFs) is of pronounced significance for their scientific research and practical application, but the regulation through external stimuli is still a challenging task. Here we prepare and electrically control the nonlinear optical regulation of conductive MOFs Cu-HHTP films with [001]- (Cu-HHTP
[001]
) and [100]-orientations (Cu-HHTP
[100]
). Z-scan results show that the nonlinear absorption coefficient (
β
) of Cu-HHTP
[001]
film (7.60 × 10
−6
m/W) is much higher than that of Cu-HHTP
[100]
film (0.84 × 10
−6
m/W) at 0 V and the
β
of Cu-HHTP
[001]
and Cu-HHTP
[100]
films gradually increase to 3.84 × 10
−5
and 1.71 × 10
−6
m/W at 10 V by increasing the applied voltage, respectively. Due to 2D Cu-HHTP having anisotropy of charge transfer in different orientations, the NLO of MOFs film can be dependent on their growth orientations and improved by tuning the electrical field. This study provides more avenues for the regulation and NLO applications of MOFs.
Nonlinear optical properties of metal-organic framework can be tuned for potential optical applications. Here the authors demonstrate an enhancement the nonlinear absorption coefficient of MOF film by applying external electric field.
Journal Article
Toward azo-linked covalent organic frameworks by developing linkage chemistry via linker exchange
Exploring new linkage chemistry for covalent organic frameworks (COFs) provides a strong driving force to promote the development of this emerging class of crystalline porous organic materials. Herein we report a strategy to synthesize COFs with azo linkage, one of the most important functional unit in materials science but having not yet been exploited as a linkage of COFs. This strategy is developed on the basis of in situ linker exchange, by which imine-linked COFs are completely transformed into azo-linked COFs (Azo-COFs). Moreover, distinct properties of Azo-COFs from their corresponding imine-linked precursors are observed, indicating unique property of Azo-COFs. This strategy provides a useful approach to develop new linkage chemistry for COFs. It also has established a synthetic method for azo-linked COFs, which not only enriches the family of COFs but also offers a platform to explore properties and applications of this class of crystalline porous conjugated polymers.
Exploring new linkage chemistry for covalent organic frameworks (COFs) provides a strong driving force to promote the development of this class porous materials. Here, the authors report a strategy to synthesize COFs with azo linkages based on an in situ linker exchange strategy which transforms imine-linked COFs into their azo-linked counterparts, and explore the unique properties of azo-linked COFs.
Journal Article
Recent Progress in Metal-Organic Framework Based Fluorescent Sensors for Hazardous Materials Detection
Population growth and industrial development have exacerbated environmental pollution of both land and aquatic environments with toxic and harmful materials. Luminescence-based chemical sensors crafted for specific hazardous substances operate on host-guest interactions, leading to the detection of target molecules down to the nanomolar range. Particularly, the luminescence-based sensors constructed on the basis of metal-organic frameworks (MOFs) are of increasing interest, as they can not only compensate for the shortcomings of traditional detection techniques, but also can provide more sensitive detection for analytes. Recent years have seen MOFs-based fluorescent sensors show outstanding advantages in the field of hazardous substance identification and detection. Here, we critically discuss the application of MOFs for the detection of a broad scope of hazardous substances, including hazardous gases, heavy metal ions, radioactive ions, antibiotics, pesticides, nitro-explosives, and some harmful solvents as well as luminous and sensing mechanisms of MOF-based fluorescent sensors. The outlook and several crucial issues of this area are also discussed, with the expectation that it may help arouse widespread attention on exploring fluorescent MOFs (LMOFs) in potential sensing applications.
Journal Article
Carbon felt modified with bismuth and asphalt-derived carbon as a high-performance electrode for vanadium redox flow batteries
Vanadium redox flow batteries (VRFBs) are among the most promising large-scale energy storage systems, owing to high efficiency, scalability, and long cycle life. However, their widespread adoption is often hindered by sluggish electrode reaction kinetics, particularly at the anode. This investigation aimed to address these limitations by introducing bismuth-doped carbon (Bi/C) nanoparticles synthesized from asphalt and bismuth onto thermally treated carbon felt (TCF) to prepare Bi and C co-deposited thermally treated carbon felt (Bi/C-TCF), leveraging the synergistic effects between the two components. The synthesis process involved spray drying followed by high-temperature calcination, resulting in a highly efficient electrocatalyst for the V 3+ /V 2+ redox couple. Electrochemical testing revealed that the Bi/C-TCF electrode significantly outperformed the conventional TCF electrode, exhibiting reduced polarization during charge-discharge cycles and enhanced catalytic activity as evidenced by its superior reaction rate constants K 0 (2.37 × 10 −2 and 2.75 × 10 −2 cm/s) compared to TCF (2.08 × 10 −2 and 2.10 × 10 −2 cm/s). In single-cell tests, the Bi/C-TCF electrode, used as the negative electrode, demonstrated superior voltage efficiency (VE) and energy efficiency (EE) across various current densities. It achieved a power density of up to 1054.3 mW/cm 2 , significantly outperforming TCF’s 825.9 mW/cm 2 . After 1000 cycles, the VE and EE remained stable at 86.2% and 85.0%, respectively, whereas the TCF cell saw a rapid decline in VE and EE to below 70% after just 515 cycles. These findings highlight the potential of Bi/C nanoparticles as a scalable and cost-effective solution for enhancing the performance and durability of VRFBs, leveraging low-cost raw materials such as asphalt.
Journal Article
Two-pole structures in a relativistic Friedrichs–Lee-QPC scheme
A general appearance of two-pole structures is exhibited in a relativistic Friedrichs–Lee model combined with a relativistic quark pair creation model in a consistent manner. This kind of two-pole structure could be found when a qq¯ state couples to the open-flavor continuum state in the S partial wave. We found that many enigmatic states, such as f0(500)/σ, K0∗(700)/κ, a0(980), f0(980), D0∗(2300), Ds0∗(2317), and X(3872), together with another higher state for each, all result from this kind of two-pole structures. Furthermore, an interesting observation is that this kind of two-pole structure will contribute roughly a total of 180∘ phase shift for the scattering process in a single channel approximation. This relativistic scheme may provide more insights into the understanding of the properties of non-qq¯ state. It is also suggested that such two-pole structure could be a common phenomenon which deserves studying both from theoretical and experimental perspectives.
Journal Article
Minimal gated unit for recurrent neural networks
Recurrent neural networks (RNN) have been very successful in handling sequence data. However, understanding RNN and finding the best practices for RNN learning is a difficult task, partly because there are many competing and complex hidden units, such as the long short-term memory (LSTM) and the gated recurrent unit (GRU). We propose a gated unit for RNN, named as minimal gated unit (MGU), since it only contains one gate, which is a minimal design among all gated hidden units. The design of MGU benefits from evaluation results on LSTM and GRU in the literature. Experiments on various sequence data show that MGU has comparable accuracy with GRU, but has a simpler structure, fewer parameters, and faster training. Hence, MGU is suitable in RNN's applications. Its simple architecture also means that it is easier to evaluate and tune, and in principle it is easier to study MGU's properties theoretically and empirically.
Journal Article
Learnware： on the future of machine learning
Current machine learning techniques have achieved great success; however, there are many deficiencies. First, to train a strong model, a large amount of training examples are required, whereas collecting the data, particularly data with labels, is expensive or even difficult in many real tasks. Second, once a model has been trained, if environment changes, which often happens in real tasks, the model can hardly perform well or even become useless. Third,
Journal Article