Tuning CO2 hydrogenation selectivity to obtain targeted value‐added chemicals and fuels has attracted increasing attention. However, a fundamental understanding of the way to control the selectivity ...is still lacking, posing a challenge in catalyst design and development. Herein, we report our new discovery in ambient pressure CO2 hydrogenation reaction where selectivity can be completely reversed by simply changing the crystal phases of TiO2 support (anatase‐ or rutile‐TiO2) or changing metal loadings on anatase‐TiO2. Operando spectroscopy and NAP‐XPS studies reveal that the determining factor is a different electron transfer from metal to the support, most probably as a result of the different extents of hydrogen spillover, which changes the adsorption and activation of the intermediate of CO. Based on this new finding, we can not only regulate CO2 hydrogenation selectivity but also tune catalytic performance in other important reactions, thus opening up a door for efficient catalyst development by rational design.
CO2 hydrogenation selectivity can be tuned by changing the crystal phase of TiO2 or simply changing the metal loadings on anatase‐TiO2 supported Ru catalysts. The essential reason for the distinctly different selectivity is the charge transfer under reaction conditions, probably as a result of hydrogen spillover, which leads to changes in adsorption and activation of intermediate CO.
Photo–thermo catalysis, which integrates photocatalysis on semiconductors with thermocatalysis on supported nonplasmonic metals, has emerged as an attractive approach to improve catalytic ...performance. However, an understanding of the mechanisms in operation is missing from both the thermo‐ and photocatalytic perspectives. Deep insights into photo–thermo catalysis are achieved via the catalytic oxidation of propane (C3H8) over a Pt/TiO2‐WO3 catalyst that severely suffers from oxygen poisoning at high O2/C3H8 ratios. After introducing UV/Vis light, the reaction temperature required to achieve 70 % conversion of C3H8 lowers to a record‐breaking 90 °C from 324 °C and the apparent activation energy drops from 130 kJ mol−1 to 11 kJ mol−1. Furthermore, the reaction order of O2 is −1.4 in dark but reverses to 0.1 under light, thereby suppressing oxygen poisoning of the Pt catalyst. An underlying mechanism is proposed based on direct evidence of the in‐situ‐captured reaction intermediates.
Photo–thermo catalytic oxidation of propane (C3H8) on Pt/TiO2‐WO3 catalyst proceeds with excellent activity at high O2/C3H8 ratios and low temperatures. An investigation of the apparent activation energy and reaction orders (relative to thermal catalysis) reveals that oxygen poisoning of the supported Pt catalyst is mitigated and performance is consequently enhanced.
Graphene continues to attract tremendous interest, owing to its excellent optical and electronic properties. Based on its unique features, graphene has been employed in the ever-expanding research ...fields. Surface-enhanced Raman scattering (SERS) may be one of the significant applied fields where graphene can make a difference. Since its discovery, the SERS technique has been capable of ultra sensitively detecting chemical and biological molecules at very low concentration, even at the single molecule level, but some problems, such as irreproducible SERS signals, should be overcome before being practically applied for spectral analysis. Graphene can be a promising candidate to make up the deficiency of a conventional metal SERS substrate. Furthermore, graphene, serving as an enhancement material, is usually deemed as a chemically inert substance to isolate the interactions between metal and probe molecules. While, irradiated by laser, structure changes of graphene under specific conditions and the contributions of its high electron mobility in plasmon-induced catalytic reactions are often ignored. In this review, we mainly focus on the state-of-the-art applications of graphene in the fields of SERS and laser-induced catalytic reactions. The advances in informative Raman spectra of graphene are firstly reviewed. Then, the graphene related SERS substrates, including graphene-enhanced Raman scattering (GERS) and graphene-mediated SERS (G-SERS), are summarized. We finally highlight the catalytic reactions occurring on graphene itself and molecules adsorbed onto graphene upon laser irradiation.
In this review, the advances in informative Raman spectra of graphene are firstly reviewed. Then, the graphene related SERS substrates are summarized. We finally highlight the catalytic reactions occurring on graphene itself and molecules adsorbed onto graphene upon laser irradiation.
Surface plasmon assisted catalysis (SPAC) reactions of 4-aminothiophenol (4ATP) to and back from 4,4'-dimercaptoazobenzene (DMAB) have been investigated by single particle surface enhanced Raman ...spectroscopy, using a self-designed gas flow cell to control the reductive/oxidative environment over the reactions. Conversion of 4ATP into DMAB is induced by energy transfer (plasmonic heating) from surface plasmon resonance to 4ATP, where O₂ (as an electron acceptor) is essential and H₂O (as a base) can accelerate the reaction. In contrast, hot electron (from surface plasmon decay) induction drives the reverse reaction of DMAB to 4ATP, where H₂O (or H₂) acts as the hydrogen source. More interestingly, the cyclic redox between 4ATP and DMAB by SPAC approach has been demonstrated. This SPAC methodology presents a unique platform for studying chemical reactions that are not possible under standard synthetic conditions.
Here, we demonstrate a facile synthesis of homogeneous Ag nanostructures fully covering the polyaniline (PANI) membrane surface simply by introducing organic acid in the AgNO3 reaction solution, as ...an improved technique to fabricate well-defined Ag nanostructures on PANI substrates through a direct chemical deposition method Langmuir 2010, 26, 8882. It is found that the chemical nature of the acid is crucial to create a homogeneous nucleation environment for Ag growth, where, in this case, homogeneous Ag nanostructures that are assembled by Ag nanosheets are produced with the assistance of succinic acid and lactic acid, but only scattered Ag particles with camphorsulfonic acid. Improved surface wettability of PANI membranes after acid doping may also account for the higher surface coverage of Ag nanostructures. The Ag nanostructures fully covering the PANI surface are extremely sensitive in the detection of a target analyte, 4-mercaptobenzoic acid (4-MBA), using surface-enhanced Raman spectroscopy (SERS), with a detection limit of 10–12 M. We believe the facilely fabricated SERS-active substrates based on conducting polymer-mediated growth of Ag nanostructures can be promising in the trace detection of chemical and biological molecules.
We demonstrate the use of amino acids as directing agents to synthesize hierarchical silver microspheres assembled by nanosheets with well-defined morphologies, in the absence of any other ...surfactants or capping agents. This fabrication method avoids the absorption of macromolecules and enables clean surface on the Ag microspheres. The chemical nature of the amino acids plays a vital role in the hierarchical structure of the Ag microspheres. As found, amino acids with simple structures and 2–3 carbon atoms like alanine and glycine lead to more loosely packed Ag microspheres, and those with more complicated structures and more carbon atoms, e.g. glycine, glutamine, and asparagine, result in close-packed Ag particles assembled by thinner nanosheets. By adjusting the concentration of AgNO3 solution, size as well as the surface roughness of the Ag microspheres can be well controlled. Individual particles of the constructed hierarchical Ag microspheres with highly roughened surface can act as sensitive SERS platforms. Detection of chemical molecules and monitoring of the plasmon-driven chemical reactions have been carried out through a single particle SERS technique.
In order to improve the accuracy of short-term travel time prediction in an urban road network, a hybrid model for spatio-temporal feature extraction and prediction of urban road network travel time ...is proposed in this research, which combines empirical dynamic modeling (EDM) and complex networks (CN) with an XGBoost prediction model. Due to the highly nonlinear and dynamic nature of travel time series, it is necessary to consider time dependence and the spatial reliance of travel time series for predicting the travel time of road networks. The dynamic feature of the travel time series can be revealed by the EDM method, a nonlinear approach based on Chaos theory. Further, the spatial characteristic of urban traffic topology can be reflected from the perspective of complex networks. To fully guarantee the reasonability and validity of spatio-temporal features, which are dug by empirical dynamic modeling and complex networks (EDMCN), for urban traffic travel time prediction, an XGBoost prediction model is established for those characteristics. Through the in-depth exploration of the travel time and topology of a particular road network in Guiyang, the EDMCN-XGBoost prediction model’s performance is verified. The results show that, compared with the single XGBoost, autoregressive moving average, artificial neural network, support vector machine, and other models, the proposed EDMCN-XGBoost prediction model presents a better performance in forecasting.
•A novel multi-agent gated collaborative signal control method is proposed.•Combining Bi-LSTM and attention establishes communication between agents.•The reward is developed to trade off the macro ...and micro control contradictions.•Simulation experiments verify the effectiveness of the proposed control model.
The macro-aggregated dynamic characteristics of urban network traffic flow encapsulated embodied in macroscopic fundamental diagram theory provide a concise perspective for network-level traffic control. However, accurately translating inter-regional macro-traffic flow control into fine-grained control at each intersection along the boundary remains challenging. To address this issue, a regional boundary intersections collaborative control method is proposed, leveraging the model-free data-driven advantages of multi-agent deep reinforcement learning. First, the proposed model develops a real-time communication module using a bi-directional long short-term memory model and an attention mechanism, enabling intersections to capture spatiotemporal features of the boundary traffic flow. Second, the feedback reward mechanism of the boundary intersection agent is meticulously constructed by considering the traffic state of the protected region, the boundary control pressure, and the traffic pressure of the intersection. The proposed model fosters cooperation at boundary intersections and delicately balances their macro-micro control contradictions based on mastering the boundary state information of the road network. Data-driven boundary gating control can fine-regulate the traffic flow distribution of the network from the perspective of macro-micro to promote its operation efficiency. The simulation experiments verify the effectiveness of the proposed multi-agent signal collaborative control method.
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