dataesr/scientific-paragraphs-categorization huggingface dataset:
The SEM micrographs (Fig. SI. 6)  show a quasi-spherical shape of nanoparticles with a uniform distribution, in agreement with the morphologies obtained from TEM data. To further confirm the presence of Fe in all samples a compositional analysis has been done also by EDS. The atomic ratio Fe/Ce obtained (average in 5 spots) is in good accordance with the theoretical molar ratio and experimental ICP data (see Table  SI. 1 for details). The optical properties of the prepared materials were evaluated by UV-Vis diffuse reflectance spectroscopy. The D(R) spectra are shown in Fig. 3a. The UV-Vis spectrum of pure CeO 2 , black line, consisted of a strong absorption band located in the 200-400 nm range where different transitions can be observed. The absorption at low wavelength, one centered at 215 nm and the other at around 275 nm (blue rectangle and green rectangle in Fig.
The rate expressions were developed, considering that ibuprofen (IBU) is adsorbed on the surface of the photocatalysts (*) leading to an adsorbed specie (IBU*), as in Eq. (2). IBU + * ↔ IBU* (2) The reversible rate expression reported in Eq. (  3 ) was adopted to describe the adsorption rate. r ADS = k ADS ⋅ ( c IBU - 1 K eqADS ⋅c IBU* ) (3) The mentioned rate expression was included in the mass balance equation valid for a batch system, see Eq. (4). dc IBU dt = -rADS⋅ρB (4) The ordinary differential equation was solved in MATLAB R2023a environment, using ode45 function, and the related adsorption kinetic and equilibrium constants were obtained by parameter estimation activity on the adsorption kinetic experiments. In detail, the objective function, defined as the square root of the squares of the residuals, was minimized using lsqnonlin algorithm.
). The occurrence of neo-formed by-product started to appear at T8, corresponding to the start of the photodegradation step, displaying a chromatographic peak at a retention time shift of 0. 3 min (3. 1 min) from the intact ibuprofen. The identification of by-product at 161 m/z assigned to the 1-ethenyl-4-(2-methylpropyl)benzene (C 12 H 16 ) was confirmed by GC-MS analysis where the fragments originated from the electron impact (IE) source were compared to the NIST database (Fig. SI. 17).
34  In another significant contribution, Yaghi et al. employed cubic (8-connected) nodes to design and synthesize a series of https://doi. org/10. 26434/chemrxiv-2023-cpvp6 ORCID: https://orcid. org/0000-0003-3365-5508 Content not peer-reviewed by ChemRxiv. License: CC BY-NC-ND 4. 0 polycubane 3D COFs with bcu topology. 35  Our research group has also made significant strides in this area, developing 3D COFs with diverse networks using either 6-or 8-connected building units,  [36] [37] [38] [39] [40]  such as the super-large porous JUC-564 with stp net,  36  the non-interpenetrated hea net exhibited by JUC-596,  37  and the mesoporous JUC-589 with a bcu net. 38  Despite these achievements, it is important to note that the structural diversity of existing 3D COFs pales in comparison to the vast repertoire of nodes available in the Reticular Chemistry Structure Resource (RCSR) database, which encompasses over 2000 networks with up to 24 extension points.
Acknowledgements This work was supported by  National Key R&D Program of China  ( 2022YFB3704900  and  2021YFF0500500 ),  National Natural Science Foundation of China  ( 22025504 ,  21621001 , and https://doi. org /10. 26434/ chemrxiv-2023-cpvp6 ORCID: https://orcid. org/0000-0003-3365-5508 Content not peer-reviewed by ChemRxiv. License:  CC BY-NC-ND 4. 0 22105082 ), the  SINOPEC Research Institute of Petroleum Processing , " 111"  project ( BP0719036  and  B17020 ),  China Postdoctoral Science Foundation  ( 2020TQ0118  and  2020M681034 ), and the program for  JLU Science and Technology Innovative Research  Team. V. V. , Q. F. and S. Q. acknowledge the collaboration in the  Sino-French International Research Network "Zeolites " framework.
This poses many challenges to the already difficult monitoring activities in the whole fisheries sector. " and "Potential environmental impacts of fisheries and aquaculture need to be assessed. " -Biomass from algae: "The FAO [comment: the Food and Agriculture Organization of the United Nations] and Eurostat databases include very fragmented information regarding the uses, economic value and market flows of algal biomass at the European level. This results from the incomplete reporting by member states and the confidentiality issues imposed by the business sector. Additionally, no information is available on the commercial use of algal biomass at national level. This limits the realistic assessment of the trade flows, for some species and countries with high internal market consumption of the biomass production.
MS fragmentation pathways of carbohydrates have been recognised and documented in well-organised nomenclature and growing databases, but unfortunately, MS fragmentation routes strongly depend on oligosaccharides' structure, including sugar (linkage) type, anomeric position, and branching. An unambiguous identification of an individual, highly complex oligosaccharide may also involve laborious separation procedures followed by various 1D and 2D proton and carbon NMR spectroscopy techniques  (Duus, Gotfredsen, & Bock, 2000). Combining of LC, MS, and NMR techniques have resulted in the recognition of >200 different human milk oligosaccharides, >100 different galactooligosaccharide structures, and numerous structures in other prebiotic mixtures, which are too often underestimated in functionality assays regarding their complexity.
For such, enzymatic and chemical methods to on-line, in between analytical columns, yield diagnostic oligomers within a range of degrees of polymerisation from 2 to 20 should be developed without losing labile substituents like arabinose, acetyl-and feruloyl groups, and methyl esters. Methods available in research should be transferred to a more routine environment while still delivering as many details as possible. Big data approaches should assist in controlling the almost unlimited flow of MS and MS n spectra from automated extraction-2D-LC-reaction-LC-MS n to identify individual oligosaccharides, and accurate and adequate databases should be built.
Acknowledgments The authors and co-authors wish to acknowledge the vision and efforts of  Dr. Patrick Navard  in creating the EPNOE project and further establishing the EPNOE Association with co-founders  Dr. Karin Stana-Kleinschek  and  Dr. Pedro Fardim. Dr. Navard  managed  EPNOE  for >15 years and under his leadership EPNOE members were able to overcome the major challenges to successfully network by creating an area of trust and collaboration. EPNOE is still a very lively organization after nearly 20 years, a proof that the foundations on which the network was built were very robust.
Acknowledgements This work was performed with financial support from  CNRS , the  University of Bordeaux , the  France-BioImaging National Infrastructure  ( ANR-10-INBS-04-01 ), the  Idex Bordeaux  ( Grand Research Program GPR LIGHT)  and the  EUR Light S&T  ( PIA3 Program ,  ANR-17-EURE-0027 ) to L. C; LH, XLG, and AR thank the  French Agence Nationale de la Recherche  (project  LAPIN -ANR-20-CE09-0021-04 ). XLG thanks  France Life Imaging  ( ANR-11-INBS-0006 ) for their financial support.
In the present paper, we discuss the recent updates to the beamline that are particularly relevant for the study of soft condensed matter systems. We first recall the main elements of the beamline layout, including the new compound refractive lenses (CRLs) focusing system. Next, we detail the new GIWAXS/GISAXS environment for studies on solid substrates, the different strategies available to catch diffraction signal from Langmuir films associated with UVvisible spectroscopy, and the recent modifications to the various facilities setups and configurations available on the beamline that are of interest to the soft matter community. Finally, we present a custom electronic notebook fully integrated to the data collection strategy of the beamline.
In-helium chamber for GIWAXS and GISAXS on solid samples Since its opening to users, SIRIUS has offered GIWAXS and GISAXS techniques for solid samples. Prior to 2021, two main sample environments were available depending on the  desired temperature range, vacuum needs and compatibility, and potential exposure to solvent vapour: a 'Baby' chamber with a beryllium dome and equipped with a high-temperature oven (1000 C)  (Ciatto et al. , 2016)  or a chamber with Kapton windows on its facade  (Fontaine et al. , 2014). However, both setups had a significant portion of the beam travelling in air from the beamline exit window to the chamber and then from the chamber to the detector. This, in addition to the numerous Kapton or beryllium windows traversed, led to a spurious background that had to be carefully accounted for in data analysis  (Galerne et al.
The direct and reflected beam scattering by helium is much lower than with air, making acquisition much more efficient and data analysis easier, particularly when looking for weak diffraction spots and diffuse scattering  (Heinrich et al. , 2023). For GIWAXS measurements, we systematically use the Pilatus3 1M detector with a fixed sample-to-detector distance between 280 mm and 400 mm. Thus, the largest q-range accessible in a single image without moving the detector is 0. 5-30 nm À1 , using a beam energy of 12 keV. The diffraction  Left: helium chamber in GIWAXS configuration. The chamber is directly connected to the beamline and the Pilatus detector via gas-tight bellows. A 200 mm-thick beryllium window in the inlet tube isolates the setup from the beamline vacuum. An oxygen sensor connected to an outlet of the chamber indicates the percentage of oxygen remaining in the chamber.
Continuous scanning is preferred to avoid sample perturbation induced by vibrations in step-bystep mode, in particular when probing liquid surfaces. This procedure also presents the advantage of reducing the deadtimes induced by the sleep times following each movement in a step-by-step scan. In such a continuous scan, the motor is slowly moved between the two extreme positions of the scanning angular range as the data are recorded on-the-fly. The speed of the motor is determined by the ratio of the angular range and the product of the number of points and counting time, with a correction factor applied to account for acquisition dead-times. A custom Jupyter Notebook is used to reduce the data and assemble scans at different values of the out-of-plane angle (see Section 4). This process yields an intensity map I(q xy , q z ), where q xy denotes the in-plane component of the scattering vector and q z its vertical component.
In this context, the SIRIUS beamline gives access to a range of detection setups and beam shapes allowing to vary the diffraction data collection at the air-water interface and tailor our approach to the needs of the systems and of the users. While the two first geometries described here, with a Soller collimator or a single slit, can be immediately used depending on their respective advantages, the third one can be seen as a prospective option, especially with the development of small beam capabilities on beamlines. Top view of the GIXD experiment without collimation system before the 2D detector with a footprint of size L Â w and the different angles to determine the resolution of the measurement at a 2 angle.
JupyLabBook: a customized electronic notebook Since mid-2020, SIRIUS users have had access to a custom electronic notebook. This interactive notebook, called Jupy-LabBook, is based on a Jupyter Notebook core (https:// jupyter. org/) enriched with several widgets (see Fig. 11 ). Designed as a low-code tool, users unfamiliar with programming can use it without writing a single line of code, after setting up of the notebook by the beamline staff, while an expert user can easily enrich it with Python code. The notebook allows users to quickly reduce and visualize data once a scan is complete, and to display the results in a clear and structured manner with headings and comments. Most of the experimental techniques present on the beamline can now be processed in the notebook, such as GIXD, GIWAXS, GISAXS, XRF, XRR and Langmuir isotherms.
The alignment process and all the calibration parameters are reported at the beginning of the notebook file, and used for data reduction throughout the experiment. JupyLabBook converts diffraction scans into reciprocal space, represented as a TIFF image and raw ASCII files, and fluorescence scans into individual energy-intensity spectra in the form of text files, and spectrograms as images. X-ray reflectivity data on solids can also be extracted as ASCII files using the notebook by integrating the 2D detector, performing proper background subtraction and normalizing by the incident beam. The notebook is linked to the log files of SPyC, an IPython-based control and acquisition system developed at SOLEIL within the TANGO framework, enabling automatic transfer of most of the information related to the scan.
For users who prefer not to display graphs and figures for each scan, the notebook allows importing only the sequence of commands typed into SPyC, similar to what was previously recorded in paper notebooks. Once the experiment is complete, the notebook can be converted into a single PDF file that includes all the relevant information. The open-source code of JupyLabBook is hosted on the SOLEIL GitLab repository (https://gitlab. synchrotronsoleil. fr/sirius-beamline/notebooks/JupyLabBook) and version 3. 0. 2 is provided here in the supporting information. While it was specifically developed for the SIRIUS beamline, the code has been structured in a way that allows for potential adaptation to other beamlines, but without support of SIRIUS staff.
Acknowledgements We would like to thank all of the  SOLEIL  staff that have been involved in the development of the beamline through the years, as well as our community of users for constant feedback and suggestions for improvement. Buildup of some setups was carried out within the framework of the MICASOL platform set between  Institut Charles Sadron (CNRS, Strasbourg, France)  and  Synchrotron SOLEIL  (https://www. ics-cnrs. unistra. fr/micasol), and in association with  Institut de Physique et Chimie des Materiaux de Strasbourg (CNRS, Strasbourg University, France). We would also like to thank  Dr Mikhail  ( Misha )  Zhernenkov ,  US DOE Office of Science, formerly at NSLSII/SMI , for fruitful discussions about Be lenses and transfocators.
Funding information The Pilatus3 1M detector was co-funded by  MICASOL  and  SOLEIL. The Langmuir trough was funded by the  RTRA  (Reseau The  ´matique de Recherche Avancee ) ' Triangle de la Physique ' and the four- element SDD XFlash QUAD 5040  by the  French Agence Nationale de la Recherche  project ' MOON ' (grant No. ANR-11-NANO-0014 ).
Carbonation experiments Kinetic and mass transfer experiments were carried out in a 300 mL autoclave reactor equipped with mechanical stirring. In typical carbonation experiment, 50 g of epoxidized methyl oleate and 4 g of the synthesized SBA-15-4PPI catalyst were mixed in the reactor vessel. The reactor was sealed and purged with nitrogen three times. Thereafter, the reaction mixture was heated to the target temperature, and once achieved, pure CO 2 was fed continuously into the system at a constant pressure. The reactor pressure was regulated by a pressure controller so   T. Salmi et al. that the CO 2 pressure remained constant during the experiment. The pressure was monitored continuously and the pressure data were stored on a PC. To ensure excellent gas-liquid mixing, a gas-entrainment impeller was used at 800 rpm.
Summary of model equations and numerical strategies The mathematical model consists of the rate Eqs. (  1 )-(  10 ), the component generation rate expressions (11)-(  14 ) and the mass balances (  24 ) and (  26 ) along with the initial conditions (27). This system of coupled ordinary differential equations (ODEs) was solved numerically as an initial value problem (IVP) with a stiff ODE solver implemented in the software package ModEst  (Haario, 2014). The values of the rate and adsorption parameters were varied systematically to obtain the best possible fit of the model to the experimental data. The search for the optimal parameter values was done with the aid of a hybrid simplex-Levenberg-Marquardt algorithm implemented in the software ModEst. The ODE solver worked under the optimization routine to provide the model predictions, i.
Conclusions An extensive experimental and modelling effort of epoxide carbonization was carried out in a laboratory-scale semibatch reactor. The catalyst contained both Lewis and nucleophilic sites, which gave inspiration for a detailed study of these sites and their mutual interaction. Experimental data were produced, describing the carbon dioxide solubility and mass transfer, the carbonation kinetics and the product distribution. Five rival reaction mechanisms were compared by nonlinear regression analysis and the formation of the side product, the ketone was studied in separate experiments in the absence of carbon dioxide. The results indicated that the dominant path to the ketone proceeds via the nucleophilic sites. As a final conclusion, it can be stated that the carbonation requires an interaction of the Lewis sites and the nucleophilic sites, while the ketone formation can proceed in the absence of the Lewis sites.
The measurement was performed on devices without scattering layer and at open circuit condition. Infrared spectra were obtained at room temperature using a VERTEX 70 FTIR spectrometer (BRUKER) in transmittance mode; DLaTGS detector. The spectra were collected with a resolution of 4 cm -1 in ATR mode, A225/Q PLATINUM ATR Diamond crystal with a single reflection accessory. The electrochemical impedance spectroscopy (EIS) data was obtained with Autolab (PGSTAT 302 N, Metrohm). EIS spectra were recorded in the dark at a potential 20 mV below the open-circuit potential of the DSSCs; a sinusoidal perturbation of potential with a peakto-zero amplitude of 10 mV in the frequency range of 100 kHz-1 Hz was applied. The EIS data obtained were analyzed using ZView software. The real and imaginary parts of the impedance are normalized (multiplied) to the sealing area of the device -0.
36 cm 2. A Shimadzu (UV-3600) UV-Vis-NIR spectrophotometer was used to obtain spectra of absorbance of the photoelectrodes and to quantify the amount of N719 dye adsorbed on the mesoporous TiO 2 layer. The amount of the adsorbed dye was determined using desorption of the dye in 0. 5 M solution of NaOH in H 2 O:EtOH (1:1, V/V). Photoanodes were immersed in 3 mL of this solution for 4 h, and the absorbance of the solution was measured. The amount of the dye was calculated using calibration data obtained by measurement of absorbance at 511 nm of the solutions with a defined concentration of the dye. The long-term stability of the devices was assessed in a chamber (Atlas SUNTEST XLS+) equipped with AM1. 5G filter, 380 nm UV-cut-off filter, and Xe-lamp as a light source. The testing protocol followed ISOS-L-2 conditions  [46] ; incident light intensity was 900 W m -2 ; the temperature of the devices stabilized at 50 ± 2 • C; cells were connected to a passive load (Fig.
Acknowledgments Daniela Rodrigues  acknowledges the  FCT-Fundação para a Ciência e a Tecnologia  for her doctoral grants  SFRH/BD/131818/2017  and  COVID/BD/152163/2021. J. Martins  acknowledges the  FCT  for his doctoral grant  SFRH/BD/119402/2019. This work was financially supported by  LA/P/0045/2020  ( ALiCE ),  UIDB/00511/2020 , and  UIDP/ 00511/2020  ( LEPABE ), funded by national funds through  FCT/MCTES  ( PIDDAC ). Project  2SMART -engineered Smart materials for Smart citizens , with the reference  NORTE-01-0145-FEDER-000054 , under the  Portugal 2020 Partnership Agreement , through the  European Regional Development Fund (ERDF). National funds  through  FCT , under the project  UIDB/00285/2020  and  LA/P/0112/2020. NMR data was collected at the  UC-NMR  facility which is supported in part by  FEDERthrough  the  COMPETE  and  FCTgrants REEQ/481/QUI/2006 ,  RECI/ QEQ QFI/0168/2012 ,  CENTRO-07-CT62-FEDER-002012 , and  Rede Nacional de Ressonância Magnética Nuclear (RNRMN).
Acknowledgement This work was supported by the  PIA   ANR  project  CaPPA  ( ANR-11-LABX-0005-01 ), the  ANR CHESS  project ( ANR-21-CE29-0027 ), the  I-SITE ULNE project OVERSEE  ( ANR-16-IDEX-0004 ), the  French Ministry of Higher Education and Research, region Hauts de France.
69 (Fig. 2 ), with -1 or 1 for an excellent correlation and 0 for no correlation. However, the trend in Fig. 2  would be expected to match with m = 1 (dashed line), as all working pressure calculation methods should give the same results within an error, or it should describe a nonlinear approach to 1 on a larger pressure scale. We used only data points where the pressure was measured under the same conditions with two different methods for Fig. 2. The dataset is small, and the range of pressure is limited to <1. 7 GPa (ruby) which lies in the nature of the experiments of this study. A nonlinear approach towards the dashed line (m = 1) can be expected for pressures >2 GPa, but at lower pressures the EOS of gold shows a clear shift towards higher pressures (Fig. 2 ) and cause probably pressure overestimation.
Pressure values calculated from gold show further unexpected behavior during each experiment, as for several runs the pressure seem to remain elevated after the last quenchingrelative to the first measured pressure before the start of the experiment. This is not in agreement with ruby fluorescence. Moreover, in experiment LN11 the pressure seems to drop during the laser heating from 1. 9 GPa to 0. 8-1. 2 GPa for the first four heating cycles but seem to increase to 2. 0 GPa after the last heating cycle (Table  2 ). A closure (volume change) of the sample chamber could not be observed. We argue therefore that pressure calculations from the EOS of gold are unreliable for the applied pressure range of this study (< 2 GPa). Pressure data in this range calculated from gold XRD are rather estimates and must be handled with care.
The gaskets of each experiment were recovered, and their thickness was measured after the run to calculate the change in the set-up geometry of the SXRF analyses during the experiments. To quantify the Br concentration in the basaltic glass, the aqueous fluid, or in neon all obtained SXRF spectra from standards and experiments were processed by using the PyMCA software  (Solé et al. , 2007). We compared the Br concentration of the starting material with the calculated values from PyMCA for the first measurement at room temperature for each experiment. If both values were not in agreement, we assumed that the basalt glass was not touching both diamonds. The initial thickness of the glass was then calculated using PyMCA by adding a water/neon layer to fit the calculated Br concentration with the value from the starting material.
, 2022). Assuming a water content between 5 and 12 wt% would lead to a factor W = 3 to 7. The amount of data for bromine concentration in melt inclusions (c mi ) are rather limited relative to the lighter halogens F and Cl. Webster et al. (2018)  compiled a dataset of 175 measurements for Br and 4710 measurements for Cl in melt inclusions. They find that primitive arc magmas have in general Br concentrations <10 μg/g. Higher concentrations are however possible:  Straub and Layne (2003)  found melt inclusions with Cl concentration of 9400 μg/g from the Izu Bonin arc. According to typical Cl/Br mantle ratios of about 300, primitive melts at the Izu Bonin arc could have Br concentrations of 30 μg/g  (Bureau et al. , 2010). But for a global Br distribution in primitive arc magmas an average concentration of 5 μg/g is more likely (e.