Photothermal catalytic C-C coupling to ethylene from CO_(2) with high efficiency by synergistic cooperation of oxygen vacancy and half-metallic WTe_(2)

Photothermal catalytic CO_(2) conversion provides an effective solution targeting carbon neutrality by synergistic utilization of photon and heat.However,the C-C coupling initiated by photothermal catalysis is still a big challenge.Herein,a three-dimensional(3D)hierarchical W_(18)O_(49)/WTe_(2) hollow nanosphere is constructed through in-situ embodying of oxygen vacancy and tellurium on the scaffold of WO_(3).The light absorption towards near-infrared spectral region and CO_(2) adsorption are enhanced by the formation of half-metal WTe_(2) and the unique hierarchical hollow architecture.Combining with the generation of oxygen vacancy with strengthened CO_(2) capture,the photothermal effect on the samples can be sufficiently exploited for activating the CO_(2) molecules.In particular,the close contact between W_(18)O_(49)and WTe_(2) largely promotes the photoinduced charge separation and mass transfer,and thus the~*CHO intermediate formation and fixedness are facilitated.As a result,the C-C coupling can be evoked between tungsten and tellurium atoms on WTe_(2).The ethylene production by optimized W_(18)O_(49)/WTe_(2) reaches 147.6μmol g^(-1)with the selectivity of 80%.The in-situ diffuse reflectance infrared Fourier transform spectroscopy(DRIFTS)and density functional theory(DFT)calculations are performed to unveil the presence and significance of aldehyde intermediate groups in C-C coupling.The half-metallic WTe_(2) cocatalyst proposes a new approach for efficient CO_(2) conversion with solar energy,and may especially create a new platform for the generation of multi-carbon products.

TopoBERT:a plug and play toponym recognition module harnessing fine-tuned BERT

Extracting precise geographical information from the textual content,referred to as toponym recognition,is fundamental in geographical information retrieval and crucial in a plethora of spatial analyses,e.g.mining location-based information from social media,news reports,and surveys for various applications.However,the performance of existing toponym recognition methods and tools is deficient in supporting tasks that rely on extracting fine-grained geographic information from texts,e.g.locating people sending help requests with addresses through social media during disasters.The emerging pretrained language models have,revolutionized,natural language_processing and understanding by machines,offering a promising pathway to optimize toponym recognition to underpin practical applications.In this paper,TopoBERT,a uniquely designed toponym recognition module based on a one-dimensional'Convolutional Neural Network(CNN1D)and Bidirectional Encoder Representation from Transformers(BERT),is proposed and fine-tuned.Three datasets are leveraged to tune the hyperparameters and discover the best strategy to train the model.Another seven datasets are used to evaluate the performance.TopoBERT achieves state-of-the-art performance(average f1-score=0.854)compared to the seven baseline models.It is encapsulated into easy-to-use python scripts and can be seamlessly applied to diverse toponym recognition tasks without additional training.

A multistage collaborative 3D GIS to support public participation

This paper presents a collaborative 3D GIS to support public participation.Realizing that public-involved decision-making is often a multistage process,the proposed system is designed to provide coherent support for collaborations in the different stages.We differentiate ubiquitous participation and intensive participation and identify their suitable application stages.The proposed system,then,supports both of the two types of participation by providing synchronous and asynchronous collabora-tion functionalities.Applying the concept of Digital Earth,the proposed system also features a virtual globe-based user interface.Such an interface integrates a variety of data,functions,and services into a unified virtual environment which is delivered to both experts and public participants through the Internet.The system has been designed as a general software framework and can be tailored for specific projects.In this study,we demonstrate it using a scene modeling case and provide a preliminary evaluation toward its usability.

Multidimensional Ni-Co-sulfide heterojunction electrocatalyst for highly efficient overall water splitting

Heterostructure engineering holds exceptional promise for the development of high-performance electrocatalysts for overall water splitting.However,production of inexpensive and high-efficiency bifunctional electrocatalysts remains a challenge.Herein,we demonstrate a simple method to synthesize a paper-mulberry(Broussonetia papyrifera)-inspired Co_(9)S_(8)@CoNi_(2)S_(4)/nickel foam(Co_(9)S_(8)@CoNi_(2)S_(4)/NF)heterojunction with high catalytic activity and stability.The process involves in situ growth of NiCo layered double hydroxide and in situ derivatization of ZIF-67,followed by the S heteroatom doping.The Co_(9)S_(8)@CoNi_(2)S_(4)/NF benefits from the heterostructure and functional advantages of multidimensional building blocks including one-dimensional(1D)nanowires,2D nanosheets and nanoparticles.The optimized Co_(9)S_(8)@CoNi_(2)S_(4)/NF heterojunction with 10% sulphur content reveals excellent electrocatalytic activity with the lower overpotentials of 68 mV for hydrogen evolution reaction(HER)and 170 mV for oxygen evolution reaction(OER)at 10 mA cm^(-2) in the 1.0 mol L^(-1) KOH solution,which is superior to the recently reported transition metal based electrocatalysts.The outstanding performance is attributed to the strong interface coupling between CoNi_(2)S_(4) and Co_(9)S_(8),the advantage of multidimensional structure and the customized electronic structure.The density functional theory suggests that the interface between Co_(9)S_(8) and CoNi_(2)S_(4) optimizes the adsorption of the multiple intermediates and further facilitates water splitting kinetics.This work offers a generic approach for heterostructure engineering design of highperformance catalytic system applications.

A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images

Greenhouse gas data collected by different institutions throughout the world have significant scientific values for global climate change studies. Due to the diversity of data formats and different specifications of data access interfaces, most of those data should be first downloaded onto a local machine before they can be used. To overcome this limitation, we present a geospatial web portal for sharing and analyzing greenhouse gas data derived from remote sensing images. As a proof-of-concept, a prototype has also been designed and implemented. The work：flow of the web portal contains four processes： data access, data analysis, results visualiza- tion, and results output. A large volume of greenhouse gas data have been collected, described, and indexed in the portal, and a variety of data analysis services, such as calculating the temporal variation of regionally averaged column CO2 values and analyzing the latitudinal variations of globally averaged column CO2 values, are integrated into this portal. With the integrated geospatial data and services, researchers can collect and analyze greenhouse gas data online, and can preview and download the analysis results directly from the web portal. The geospatial web portal has been implemented as a web application, and we also used a study case to illustrate this framework.