dataesr/scientific-paragraphs-categorization huggingface dataset:
The acquisition and fitting of spectra were performed with Thermo Avantage software, whereby a Shirley background was used. The binding energy scale was calibrated with respect to the C1s peak located at 284. 8 eV. Electrochemical characterizations were performed after deaeration of the electrolyte using an argon flow. Cyclic voltammograms and electrochemical impedance spectroscopy were recorded using a Voltalab potentiostat (from Radiometer) in a three-electrode configuration setup using a Pt plate and a saturated calomel electrode (E°S CE = 242 mV vs. NHE) as counter electrode and reference, respectively. The clathrochelate complexes were dissolved in acetonitrile to a final concentration of 0. 2 mM when characterized in the homogenous phase and in dimethylfluoramide when characterized in the heterogeneous phase, using 0.
ACKNOWLEDGMENTS The authors gratefully acknowledge  Dr. François Brisset  for technical support with SEM characterization. Joumada Al Cheikh was indebted to a PhD scholarship of  Azm & Saade Association (Lebanon). Momentom IRS  project from  IDEX Paris-Saclay  is acknowledged for funding. This work was supported by a public grant provided by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" program  ( Labex Charmmmat ,  ANR-11-LABX-0039-grant ).
Acknowledgments The authors acknowledge the  LABEX iMUST  ( ANR-10-LABX-0064 ) of  Université de Lyon , within the program " Investissements d'Avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR)  and the  Agence pour le Developpement de l'Environnement et la Maîtrise de l'Energie (ADEME). This paper is dedicated to the memory of  Georges Olah.
Characterization of Fe3-xYxO4 Transmission electron micrographs (TEM) and selected-area diffraction patterns were collected with a Jeol JEM 2100 transmission electron microscope operating at 200 kV for Y05 and Y10 samples. TEM examination for Fe3O4 was performed using a FEI Tecnai T20 microscope operating at 200 kV. The samples for analysis were prepared by dispersing the powders in acetone and dropping the suspension on a lacey carbon film supported on a 300-mesh copper grid. In order to refine the crystal structure and determine the crystallite size and strain, X-ray powder diffraction (XRPD) data for all three samples were collected on a PANalytical X'pert PRO MPD diffractometer in reflection mode using CuKα1,2 radiation. The data were collected in the 2θ range from 10 to 120 o in steps of 0.
Microstructure analysis The phase composition and crystal structure of the prepared samples, Y00, Y05 and Y10, were investigated by ICP-OES, EDX, XRPD, TEM and SAED. Diffraction data indicated that all samples crystallized in the spinel type structure, space group Fd 3 m. A small amount, less than 1%, of other phases were detected in diffraction patterns for all three samples. This will be discussed in detail in the next sections. TEM (Fig. 1 ) revealed that Fe3O4 (Y00) particles are pseudospherical with mean particle size of ~ 30 nm. Analysis of TEM micrographs of Y05 showed that particles with different morphologies were formed: predominantly pseudo-spherical particles with mean diameter of about 50 nm and nanorods with mean length of ~80 nm and width of ~11 nm (Fig. 1 ). In the case of Y10, a larger quantity of nanorods was formed in comparison with Y05.
Crystal structure and XRPD line broadening analysis The collected XRPD data were used to refine structural and microstructural parameters (crystallite size and strain) of the samples prepared at 200 °C. The refinement was performed with the program Fullprof, which enables simultaneous refinement of both the structural and A c c e p t e d M a n u s c r i p t microstructural parameters, such as: lattice parameters, atomic coordinates, site-occupancies, thermal parameters, crystallite size, and strain. The background intensity of each pattern was refined using linear interpolation between selected points. Refinements continued until convergence was reached. Refined crystal structure and microstructure parameters are given in  Table 1. Fig. 4a-c  show good agreement between experimental data and structure models.
Acknowledgement: The authors would like to thank  NATO  for the  Collaborative Linkage Grant  awarded to the consortium of CATALTEX, a  Multi-Year  Project entitled " Self-Decontaminating Smart Textiles for Chemical Warfare Degradation" in the framework of "Science for Peace and Security" (SfP 984842 ). A. M. Ferraria also thanks the  Fundação para a Ciência e a Tecnologia FCT  for  UID/NAN/50024/2013  project and grant  SFRH/BPD/108338/2015.
Acknowledgements The authors are grateful for the funding support from the  National Aeronautics and Space Administration  in support of the  Mars Oxygen ISRU Experiment  (award number  NNH17CH01C ), and from  Exelon Corp  (award number  025610-00007 ). The authors acknowledge the facility support from the  Microsystems Technology Laboratories and the Center for Materials Science and Engineering (NSF  under award number  DMR-1419807 ) at  MIT. This research used the synchrotron radiation facilities at the  National Synchrotron Light Source II  ( 23-ID-2  beamline), a  U. S. Department of Energy (DOE) Office of Science User Facility  operated for the  DOE Office of Science by Brookhaven National Laboratory  under Contract No. DE-SC0012704 ; the  Advanced Light Source  which is supported by the  DOE Office of Basic Energy Sciences  under Contract No.
Acknowledgments This project was supported financially by  ANRT , a PhD grant through a  CIFRE program  n°2012/1516, AQYLON and  EDF R&D Company  and the  Program "Investissements d'avenir" (Investment for the Future)  of the  Agence Nationale de la Recherche (National Agency for Research) of the French State  under award number  ANR-10-LABX-22-01-SOLSTICE. The authors thank the  University of Reims (J. -F. Henry ,  M. Chirtoc  and  D. Caron ) for their scientific support. The authors also thank  Jeremy Valette  ( CIRAD ) for the many characterizations carried out.
The POLYPHEM project is a research and innovation action funded by the European Union's H2020 program. The project started in April 2018 and will end in March 2022. It is implemented by a European consortium of 4 research centers and 5 industrial partners. The aim of this project is both to increase the flexibility and improve the performance of small solar tower power plants. The POLYPHEM concept consists in implementing a combined cycle formed by a solarized micro gas-turbine and a Rankine organic cycle machine, with an integrated thermal storage device between the two cycles. The need for cooling is minimal. Developed from a technology already patented by CNRS and CEA, the pressurized air solar receiver is integrated in the micro-turbine cycle. The thermal efficiency targeted for the receiver is 80% with a cost of 400 €/kW.
A low primary current is necessary to avoid the saturation of the 32 S -signal that would lead to an underestimation of the sulfur isotopic fractionation δ34S V-CDT. ToF-SIMS analyses were performed using a ToF-SIMS V spectrometer (IonToF -Munster Germany). The spectrometer was operated at a pressure of 10 -9 mbar. A pulsed 25 keV Bi + primary ion source was used for analysis, delivering 0. 03 pA over a 100 x 100 µm² area. 2D spectra of negatively charged ions were recorded. Each sample was analysed two times on two randomly selected areas. Data acquisition and post-processing were carried out using Surface Lab 6. 7 software. Before each measurement, the extreme surface was sputtered for a period of 10s using a Cs + ion sputter gun to remove any surface contamination. The sputter gun used delivered 120 nA over a 500 x 500 µm² area.
Peak-fitting method using CasaXPS software ToF-SIMS peak-fitting has been already done in different studies. In the work of Cliff et al. [45] , a peak-fitting algorithm was developed to remove interferences of Al -and 13 C 14 N -from 12 C 15 N -, because in this work low mass resolution was used. More recently, the fit of ToF-SIMS spectra using CasaXPS software was done in the work of Abel et al. [46]. The aim of their peak-fitting method was to correlate the peak shape, including both full width at half-maximum FWHM and asymmetry, to surface information such as roughness and oxide thickness. They use of a mathematic function combining Lorentzian (70%) and Gaussian (30%) with the addition of an asymmetry factor, allowed them to establish a link between the asymmetry factor and the FWHM with the oxide thickness and the roughness.
The same methodology was used by Shimizu et al. [47]  and Dou et al. [48]. 13  Here, CasaXPS software was used for data processing. This software is commonly employed for the processing of XPS and Auger data. Recently, a module for processing ToF-SIMS data has been added  [49]. One of the main differences between XPS and ToF-SIMS data processing, in terms of peak-fitting, is the asymmetry of the peak side and the background. While the peak shape and the background are directly associated to physical phenomena in XPS (these are correlated to an electronic emission process)  [50] [51] [52] , the physical parameters related to the peak shape have not been yet clearly identified for ToF-SIMS measurements. In our work, the CasaXPS software was used to determine the functional of the instrumental response, allowing us to fit the peaks, without considering any specific physical factor.
This deformation could modify the trajectory of secondary ions and result in fractionation of isotopes having different masses. In summary, using ToF-SIMS as an analytical technique, combining the analysis with data processing using CasaXPS software and a proper statistical analysis of the data allows to distinguish between the origins of the two iron sulfides. To apply this approach to the analysis of other samples, on which the iron sulfide layer is heterogeneous in thickness (e. g. localized sulfides forming islands on the surface), local sulfur isotopic fractionation measurement will require both high lateral and high mass resolutions.
The mathematical model used is given by equation (  2 ). The input variables are cell's electrical parameters (series (R s ) and shunt (R sh ) resistances, ideality factor (n), and saturation current (I 0 ). ), Standard Test Conditions and climatic data (ambient temperature, irradiation and wind speed). The influence of sub-Saharan African climatic conditions on solar module has been studied by Kata et al. [11]. The module electrical parameters are obtained from the hybrid algorithm based on analytical and Levenberg-Marquardt algorithms that we developed and validated  [12]  (Fig. 3 ). The temperature and sun irradiation used for simulation were measured in real condition (sub-Saharan condition) at the same time by temperature sensor PT100 and a pyranometer. I ¼ I ph À I 0 exp qV nK B T À 1 ! À V þ R s I R sh ð2Þ I oin ¼ I phin À V ocref R shin exp qV ocref nK B T ref À 1 ð3Þ R shin ¼ V mref þ I mref R sref À Á I phin À I mref À I oin exp q V mref þI mref R sin ð Þ nK B T ref À 1 ð4Þ R sin ¼ R soin À 1 q nK B T ref I oin exp qV ocref nK B T ref ð5Þ I phin ¼ R sin þ R shin R shin I scref ð6Þ R soin ¼ V ocref À V mref 2I mref ð7Þ R shoin ¼ V mref I scref À I mref ð8Þ where K B is the Boltzmann constant, q is the charge of electron, R sin is the initial series resistance, R shin is the initial shunt resistance, R soin is the reciprocal slope of initial I-V curve at open-circuit condition, I phin is the initial photo-generated current, I oin is the initial dark saturation current, V ocref is the reference open circuit voltage, V mref is the reference maximum output voltage, I mref is the reference maximum output current, I scref is the reference short circuit current and T ref (25 °C).
Thus, the ships route schedules could be dynamically optimized taking into account weather forecast in order to maximize their capacity factors (CF). The aim of this study is to investigate how high the capacity factors of energy ships could be when using weather-routing and compare them to that of stationary wind turbines that would be deployed in the same areas. To that end, a modified version of the weather-routing software QtVlm was used. Velocity and power production polar plots of an energy ship that was designed at LHEEA were used as input to QtVlm. Results show that capacity factors over 80% can be achieved with energy ships and stationary offshore wind turbines deployed in the North Atlantic Ocean.
Optimization criterion In the standard version of QtVlm, the optimization criterion is the travel duration from the starting point A to the arrival point B. QtVlm uses the isochrones method to find an optimal route. The isochrones method  [4]  is a practical deterministic method for finding the minimum time route obtained through varying ship headings while assuming constant engine power  [8]. The software includes the possibility to further improve the travel duration by optimizing the location of the nodes of the optimal route using the simplex method. A dedicated version of QtVlm was developed in order to be able to optimize the capacity factor over the route instead of the travel duration. The new optimization criterion is defined by:  (.
Floating wind turbine capacity factor using QtVlm The assessment of the capacity factors for stationary 5MW floating offshore wind turbines hypothetically deployed in the North Atlantic ocean also has been performed using the QtVlm software. In that case, the polar plot for the velocity were set to zero and the polar for the power was derived from the wind turbine power curve (Figure  1 ). Extrapolated wind data at the altitude of the hub (90m) using power law profile  [13]  has been used to calculate the CF for stationary wind turbine.
Acknowledgements The authors acknowledge nancial support from the  Xunta de Galicia (Regional Government, Spain)  under the project  ED431C 2016-034  and from the  Spanish Ministerio de Economía y Competitividad  under the project  CTM2017-84050-R. M. T. -A. and M. A. R. -D. acknowledge nancial support from the  Xunta de Galicia (Regional Government, Spain)  under grants  2017 ED481A.
For further comparison, ex situ grazing incidence extended Xray fine structure (GI-EXAFS) data of MoS 2 films were recorded before and after stability measurements. The Fouriert ransform (FT) profiles in R-space (Figure  2b, c )p resent two main peaks at 2. 40 and 3. 16 (Table  1 ) correspondingt ot he nearest MoÀSa nd MoÀMo bonds, respectively. T he coordination number (CN) values shown in Table  1s  uggest that there is no complete shell of Satoms around the central Mo at the surface of the MoS 2 films, which can be due to termination by Mo edges or oxidation by emersion from the electrolyte and air ex- posure. [22] By contrast,F Tc urves of 1T-MoS 2 exhibit ad istinct decreaseo ft he MoÀMo bond length (short MoÀMo bond) from 3. 16 to 2. 75 (Table1), which corresponds to the characteristic bond length found in 1T phase MoS 2.
Acknowledgements This work is part of the program"  CO 2 -neutral fuels " ( project1 3-CO26 ) of the Foundation for Fundamental Researcho nM atter (FOM), which was financially supported by the  Netherlands Organization for Scientific Research( NWO). This research program was co-financed by  Shell Global Solutions InternationalB. V. A. S. and A. A. B. acknowledge financial supportf rom the  European Research Council  (Grant Agreement No. 648787-ALDof2DTMDs ). Dr. Lu Gao  and  Jan Wiesfeld  from  Eindhoven University of Technology  are thankedf or their help in SEM measurementsa nd 1T-MoS 2 preparation. Chunguang Chen  and  Prof. Dr. P eter H. L. Notten  from  Forschungszentrum Jülich, Germanya re  acknowledged for fruitful discussions.
FTIR-ATR spectroscopy A first analysis consists of finding the main compounds present in the samples by FTIR-ATR spectroscopy. Major constituents of sand are Calcite (CaCO3), Dolomite (CaMg(CO3)2) and Quartz (SiO2). Their characteristic peaks are detailed below (Fig. 8 ). Only the common size fraction 100µm < Ø < 200µm of the Moroccan sands has been analyzed by FTIR-ATR spectroscopy in qualitative terms. This equipment is provided with a diamond tip making noise in the spectra between 1900 and 2400 cm -1. Thanks to a database for minerals  [31] , the peaks obtained between 2600 cm -1 and 350 cm -1 (Fig. 9 ) reveal the presence of these three main compounds. It can be noted that they appear in variable quantity for each sand sample according to the intensity of their peaks. Therefore, it can be shown that sand from Boujdour is a carbonate-rich sand, contrary of sand from Ouarzazate, which is a quartz-rich sand.
X-Ray Diffraction The second analysis is made by XRD to know the quantity of each mineral in every samples. The characteristic peaks for Calcite, Dolomite and Quartz are detailed below (Fig. 10 ). These three compounds can be easily differentiated because their main peak doesn't have the same position and the same intensity. Figure  11  illustrates the mineralogical composition of the Moroccan sand samples on the same size fraction as previously, analyzed by XRD. All the diffractogramms reveal the same peaks between 10° and 75°, but they appear with different intensity. Thanks to a database for minerals  [31]  and the intensity of the peaks, we can reveal the presence of the three main compounds and their approximate quantity. Therefore, it can be shown that sands from Boujdour, Laâyoune and Temara are carbonate-rich sands, contrary of sands from Ouarzazate and Skoura, which are quartz-rich sands.
Acknowledgments The authors would like to acknowledge the Moroccan organizations  MASEN Site Operations team and MAsCIR , which provided the different sand samples. The research leading to these results is realized in the frame of the  MASEN-CEA durability project , the  WASCOP  project which has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No. 654479 , and also from French national funding from  Agence Nationale de la Recherche  on the program Investissements d' Avenir  (n°  ANR-11-EQPX-0014 ) for some equipments.
Acknowledgements We would like to acknowledge the  University of North Carolina at Chapel Hill  for start-up funds, which supported this work. This work was performed in part at the  Chapel Hill Analytical and Nanofabrication Laboratory, CHANL , a member of the  North Carolina Research Triangle Nanotechnology Network ,  RTNN , which is supported by the  National Science Foundation , Grant  ECCS-1542015 , as part of the  National Nanotechnology Coordinated Infrastructure, NNCI. C. R. acknowledges the funding of the  CNRS  and the  Agence Nationale de la Recherche  ( ANR-17-CE09-0034-01 , " SEE ").
∆ 2θ are the Bragg peak FWHM of the synthesized samples and the standard WO3 sample obtained after a thermal treatment of 24 h at 1000°C, respectively. The as-prepared primary powder was submitted to thermal and thermogravimetric analyses using a SETARAM TGA/DTA 92. The thermal decomposition was studied under air, in the 25-800°C temperature range with a heating/cooling rate of 5°C. min -1. The morphologies of the WO3 samples were observed using a SUPRA 40Vp Gemini Zeiss scanning electron microscope (SEM) operated at 5 kV. All particle sizes were determined using the Image-J software. The UV-Visible diffuse reflectance spectra (DRS) of different samples were recorded using a LAMBDA 190s UV/Vis/NIR spectrometer along with a 150 mm integrating sphere and using BaSO4 as background reference. A small volume powder sample was compacted in a manual press into a 1.
Photoresistance: The resistance of the samples is measured using a Keithley digital multimeter, which recorded the data as a function of time. The PS and NP WO3 powders were dispersed in solution and deposited dropwise on the surface of a SiO2/Si wafer covered with Pt electrodes. The electrodes are arranged in interdigitated combs favouring a better contact with the WO3 oxides. Both samples were dried at room temperature and then treated at 500°C. The resistance changes were obtained after exposure to solar radiation for 90 sec, then followed by measurements in the dark.
The lipid samples were then prepared in order to inject 25 nmol of total fatty acids dissolved in 100 µL of chloroform/methanol [2/1, (v/v)] containing 125 pmol of each internal standard. The membrane lipids were separated by HPLC (Agilent 1200) equipped with a diol column (150 mm x 3 mm x 5 µm; Macherey-Nagel) at 40°C and quantified by MS/MS with a triple quadrupole mass spectrometer equipped with a jet stream electrospray ion source (Agilent 6460)  (Jouhet et al. , 2017; Pittera et al. , 2018). Mass spectra were processed with the Agilent MassHunter Workstation software for lipid identification and quantification. Lipid amounts (pmol) were.
Accepted Article of the four desaturase clusters of likely orthologous genes (CLOGs) from the Cyanorak database based on their best hit sequence and read counts were normalized to the average gene length of each CLOG. In order to study the presence/absence of lipid desaturases with regard to thermal environments, only stations dominated by major Ecologically Significant Taxonomic Units (ESTU) of Synechococcus clades I to IV, namely ESTUs IA, IIA, IIIA or IVA-C sensu  (Farrant et al. , 2016) , were used. Furthermore, to ensure sufficient coverage for the results to be reliable, only stations with a minimum of 2,500 distinct CLOGs, corresponding to the average number of genes in Synechococcus genomes, were considered. Altogether 52% (33 out of 63) of the Tara Oceans stations have been retained for the analysis.
Metagenomics of lipid-desaturase genes Previous studies have shown that marine Synechococcus temperature ecotypes display different sets of genes encoding lipid-desaturases, including the 9-desaturases DesC3 and DesC4 and the 12-desaturases DesA2 and DesA3 (Notes S3;  Varkey et al. , 2016; Pittera et al. , 2018). In order to complement the results obtained on strains representative of cold-(I and IV) and warm-adapted (II and III) clades, we used the Tara Oceans dataset to study the global distribution and prevalence of the four desaturase genes along natural thermal gradients (Fig. 6 ). The prevalence of the desC3 gene was close to 1 at all stations, independently of the seawater temperature and ESTU composition (Fig. 6B ). This shows that this desaturase gene is present in all Synechococcus cells in situ in a single copy, just like petB.
By contrast, the desC4 gene was virtually absent from waters warmer than 20°C (Fig. 6C ). Below this threshold, the prevalence of this gene increased quasi linearly as seawater temperature decreased, reaching values close to 1 in 13°C waters. This gene was most abundant in populations colonizing waters below 17°C, dominated by Synechococcus ESTUs IA and IVA-C  (Farrant et al. , 2016). The prevalence of the desA2 gene, which encodes a 12-desaturase inserting a double unsaturation, showed its maximal value of c. a. 1 for temperatures higher than 20°C (Fig. 6D ). Below this temperature, the prevalence progressively decreased down to zero for seawater temperatures lower than 14°C. In this dataset, the desA2 gene is mostly present in populations dominated by Synechococcus ESTUs IIA and IIIA. The other 12-desaturase, desA3, showed a similar global pattern to the desC4 gene with a marked shift in the relative abundance of this gene between populations dominated by Synechococcus ESTUs IA and IVA-C, colonizing waters below 18°C and those dominated by ESTU IIA, thriving in waters above this temperature.