dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments: This research was assisted by the  Department of Polymer Engineering, National Textile University, Faisalabad, Pakistan , and the  Department of Chemical Engineering, COMSATS University Islamabad CUI, Lahore Campus, Pakistan , by providing lab facilities. We would also like to express our thanks to the  School of Chemical and Materials Engineering, National University of Science and Technology, Islamabad, Pakistan , for assisting during the course of this research. Nasir M. Ahmad  acknowledges the support of  HEC   NRPU  Project no. 6020.
Nanoparticle tracking analyse (NTA) For the determination of number of IONPs per unit volume in magnetic suspensions with iron contents of 0. 5 and 1 g Fe L À1 , we employed Nanosight NS300 (Malvern Instruments, USA). The 0. 5 and 1 g Fe L À1 samples were diluted 1 : 5000 in DDW and injected into the instrument chamber using a 1 mL syringe. Camera settings were adjusted in order to focus the objective. The video data was collected for 60 seconds and repeated 3 times per sample.
Acknowledgements Authors are deeply acknowledged to the funding by  Spanish Ministry of Science, Innovation and Universities  ( MAT2017-85617-R ,  MAT2017-86540-C4-1-R ,  RTI2018-095303-A-C52 ,  SEV-2016-0686 ,  PEJ2018-005496-A  and  PID2019-106301RB-I00 ) and  Comunidad de Madrid (NANOMAGCOST ,  S2018/NMT-4321 , and  PEJ-2017-AI/IND-6283 ). Spanish Scientic Network (Hipernano ,  RED2018-102626-T ),  European COST  Actions  CA17115  (MyWave), and  CA17140  ( Nano2Clinic ) are also acknowledged. Authors thanks  David Sigüenza  and  Rebeca Amaro  ( IMDEA Nanociencia ) for their support in nanoparticle preparation and characterization. A. E. and A. S. acknowledges the nancial support from the  Comunidad de Madrid  for an " Atracción de Talento Investigador " ( 2018-T1/IND10058  and  2017-t2/ IND5395 ).
Acknowledgment This work was supported by the  National Natural Science Foundation of China  (Grant No. 11902223 ), the  Shanghai Pujiang Program  (Grant No. 19PJ1410100 ), the program for professor of special appointment ( Eastern Scholar ) at  Shanghai Institutions of Higher Learning , the  Fundamental Research Funds for the Central Universities , and the  High-Level Foreign expert Program. This work is also partially supported by the  French EIPHI Graduate School  (contract " ANR-17-EURE-0002 ").
As the metal are non-numerical factors, no zero level can be applied for this parameter. Therefore, two CCDs were conducted: one for Pt  (11 experiences ) and the second one for Pd (11 experiences), equaling 22 experiences for both metals. When varying all the parameters, a matrix was built using the "Minitab" software. The responses studied were the FF conversion, the MA and FA yield, and the MA and FA selectivity. then added and the pH was adjusted to 2 by the addition of H2SO4. Two hours later, the catalyst was filtered using a filter paper and a Büchner funnel, washed with hot water at 70 °C (3 times, 30 mL each) and ethanol (3 times, 30 mL each), and dried overnight at 80 °C. S1 ) to study two different parameters (metal loading and metals ratios). The sol-immobilization method was applied (Figure  10 ) to deposit Au, Pd, and Pt NPs onto the surface of TiO2, in which the total metal loading and metal ratio (Au:Pd and Au:Pt) were varied.
Hence, the total number of conditions for the CCD was 11 by each metal as calculated: 2 n + 3 repetitions at 0 level (where n = 2, the number of factors in this study, and 3 is the number of levels). As the metal are non-numerical factors, no zero level can be applied for this parameter. Therefore, two CCDs were conducted: one for Pt (11 experiences) and the second one for Pd (11 experiences), equaling 22 experiences for both metals. When varying all the parameters, a matrix was built using the "Minitab" software. The responses studied were the FF conversion, the MA and FA yield, and the MA and FA selectivity. The prepared catalysts were characterized by using different techniques. X-Ray Diffraction (XRD) analysis was performed using a Bruker D8 Advance Powder X-ray diffractometer (Billerica, MA, USA) to determine the morphology of the prepared catalyst.
Acknowledgments: The REALCAT platform benefits from a state subsidy administered by the French National Research Agency (ANR) within the frame of the 'Future Investments' program (PIA) with the contractual reference ANR-11-EQPX-0037. The European Union, through the ERDF funding administered by the Hauts-de-France Region, has co-financed the platform. Centrale Lille, the CNRS, and Lille University, as well as the Centrale Initiatives Foundation, are thanked for their financial contributions to the acquisition and implementation of the equipment of the REALCAT platform. The Chevreul Institute (FR 2638) and the Ministère de l'Enseignement Supérieur, de la Recherche, et de l'Innovation are also acknowledged for supporting and partially funding this work.
Thermoplastic Material Extrusion Printing Current collector 3D discs (11mm diameter, 200µm or 1mm thick) were designed by means of Autodesk Fusion 360 software, after which they were divided into 100µm thick 2D slices using PrusaSlicer software and printed by a Prusa MK3S 3D printer (Prusa Research, Czech Republic) to perform further EIS and cyclic voltammetry. Nozzle ordinary input and output diameters of 1. 75 and 0. 4mm, respectively, were employed. The highest resolution in the Z direction is 200µm for the first layer and 50µm for the following. The nozzle temperature was set 20 °C higher than the melting temperature of the composite film and the fan settings were set to 100%. Bed temperature was set to 60 °C to favor the adherence of the first printed layer. Prior to printing each sample, the nozzle was purged thoroughly by printing a 2cm 3 purge cube with the corresponding filament.
Differential Scanning Calorimetry (DSC) Thermal characterization of films, filaments, and 3D printed discs was carried out by means of a DSC204F1 supplied by NETZSCH-Gerätebau GmbH, Germany. All prepared samples were characterized between -60 and 300C at a heating rate of 10Cmin -1 under argon atmosphere (50mlmin -1 ), using about 10mg of sample of each composition. Heat flow data from the first heating operation were recorded.
Main values are summarized in Table  2. As expected, the crosslinking increased (i) with a lower Rw, from 2680 to 4900 mol. m -3 for XP2-1R8 and XP2-1R1, respectively. It also increased (ii) with a higher NCO/OH ratio, respectively, with 4269 and 8508 mol. m -3 for XP2-1R2 and XP6-1R2, and (iii) by replacing SPU by TEOS. The results also confirmed the lower crosslink densities of XP4-1R2 and XPT3-1R2 which explained the decreased Tg and Tα observed earlier in DMA and DSC. Uniaxial tensile tests were performed to analyze the static mechanical properties of the xerogels. The curves are displayed in Figure  6  and corresponding data are summarized in Supporting Information (Table  SI. 1). All xerogels based on the SPU2-1 polymer exhibited similar Young's moduli, at around 19 ± 3 MPa. When comparing the xerogels by Serie, the Young's moduli seemed mainly dependent on the organic PU content and architecture, and not on the inorganic crosslinking density.
Moreover, in Series 1 when Uniaxial tensile tests were performed to analyze the static mechanical properties of the xerogels. The curves are displayed in Figure  6  and corresponding data are summarized in Supporting Information (Table  SI. 1). All xerogels based on the SPU2-1 polymer exhibited similar Young's moduli, at around 19 ± 3 MPa. When comparing the xerogels by Serie, the Young's moduli seemed mainly dependent on the organic PU content and architecture, and not on the inorganic crosslinking density. Moreover, in Series 1 when the organic phase was increased from XP2-1R2 to XP4-1R2, the elastic modulus significantly increased from 21 to 79 MPa, probably from the higher organic content and urea bonds forming physical interactions. Here, XP6-1R2 was not tested since it was too fragile to properly obtain dumbbells.
Electronic structure calculations The electronic properties of optimized structures were studied using an all-electron approach and employing a numerical atom-centered (NAO) orbital basis set. These calculations were carried out using the Fritz Haber Institute ab initio molecular simulations (FHI-AIMS) program package. 48 A light grid and tier-1 basis set is used, which lead to a similar quality to a valence triple-ζ z G y O b (G O b. 27  Due to the presence of heavy atoms such as W (Z=74), relativistic effects were accounted for through the zeroth order regular approximation (ZORA)  49, 50  to the Dirac equation, which has been shown to be accurate yet computationally affordable. We noted that relativistic effects were especially relevant for medium size NPs (see Figs. S1  and S2 ). For the sake of coherence with the level of theory employed for the geometry relaxation, electronic structure calculations were also carried out by using the GGA PBE and the hybrid PBE0  51  at the PBE structure.
In particular, two different approaches were used here: the one-shot GW approximation (G 0 W 0 ) above mentioned and the more accurate eigenvalue partially self-consistent GW (evGW), where the self-gy (∑ w h partial self-consistency in the eigenvalues, while keeping the KS MO coefficients unchanged. The so-called G 0 W 0 approach has been applied to a large dataset of molecular systems  63  with excellent agreement to experiments and also successfully applied to TiO 2 NPs. 31, 32 The GW calculations provide QP energies related to physical quantities, such as the electron injection/extraction energies, that can be directly compared with photoemission spectroscopy data. 64 Furthermore, GW techniques beyond G 0 W 0 also present the advantage of providing QP energies which are less dependent on the amount of non-local exchange fraction in the starting DFT functional with respect to the KS energies.
Acknowledgements This work was partially supported by the  Fondation Nanosciences (Université Grenoble Alpes, France)  through the  M-O-Films  project. J. P. -L. acknowledges funding by the  European Research Council   Starting Grant  microCrysFact (ERC-2015-STG No. 677020 ) and the  Swiss National Science Foundation  ( project no. 200021_181988 ). J. P. -L. and D. M. -R. acknowledge support from the  European Union 's  Horizon 2020 FETOPEN-1-2016-2017 research and innovation program  under Grant Agreement  801464.
Acknowledgments The authors are grateful for the financial support received from all  SEDIFLUV  project partners, France; the  Paris' Region, France's Navigable Waterways Authority (VNF/DTBS) ,  Clamens and Cerema. The authors thank Cerema and  Gustave Eiffel university  for allowing the creation of the joint research team entitled '' Équipe de Recherche Commune sur les Matériaux pour une Construction Durable (ERC MCD )'', within which these research works were carried out.
X-ray absorption spectroscopy (XAS) In situ XAS data collection. The in situ XAS data were collected at the BM23 beamline  [40]  of the European Synchrotron Radiation Facility (ESRF) using the Microtomo reactor cell  [41] , developed by the ESRF sample environment group. The powdered Cu-CHA catalysts were prepared in the form of self-supporting pellets with masses optimized for transmission-mode XAS measurements (ca. 100 or 120 mg, resulting in Δμx = 0. 5 or 0. 3 with total absorption after the edge of μx = 2. 5, for Cu-CHA 0. 5_15 and 0. 2_15, respectively) and placed inside the reactor cell. The temperature of the sample was controlled by the heating system integrated in the Microtomo cell. The total gas flow rate and the composition of the feed were adjusted by a set of mass flow controllers; we have used a total flow rate of 100 ml/min in the XAS measurements.
The ALS procedure starts from this initial estimate, calculating and refining S and C in each iterative cycle until conver- gence is achieved. Along with this process, different constraints can be applied in order to nudge the result towards a chemically interpretable solution. The algorithm convergence is controlled through a figure of merit called Lack of Fit (%LOF), which should not change more than 0. 1% between two consecutive iterations at convergence  [46]. In the present work, PCA and MCR analyses were carried out by merging the XANES spectra (93 spectra with 124 energy points per spectrum) for all experiments in a global dataset. The MCR-ALS routine was run within a three-PCs model based on PCA outcomes and initialized through the SIMPLISMA method  [48]. As constraints, we imposed the non-negativity of the spectral and concentration profiles together with the mass balance condition which, for each scan, foresees the sum to 1 of the concentration values for each chemical species  [49].
The refinement converged after 21 iterations with a final %LOF value of 0. 57 and a percentage of variance of 99. 997%. The output of the algorithm is the MCR-ALS-retrieved XANES spectra S and concentration profiles C. The quality of the reproduction of the experimental dataset is expressed in terms of %R factor : where D and D PCA are the original and the PCA reconstructed dataset, while the sub- scripts i and j are the respective rows and columns.
Principal component analysis (PCA) and multivariate curve resolution (MCR) of in situ XANES The estimation of the number of spectroscopically distinguishable chemical species causing the XANES spectral variations observed in Fig. 3  and the subsequent isolation of their related spectral contributions has been realized by considering the entire XANES data set in the three measurements. The principal components (PCs) present in the XANES dataset are then identified by applying PCA on this data set. This approach allows to lower the ambiguity in the reconstruction typical of the MCR-ALS algorithm, which results in an improved identification of the PCs and the corresponding concentration profiles  [15]. First, the variance related to each principal component (PC) is plotted in the so-called scree plot (Fig.
4a )  [39]. PCs related to chemically or physically interpretable phenomena are characterized by high variances, while a low and approximately stable variance points to noise effects. The elbow of the scree plot curve, which divides the signal-related PCs from the noise-related ones thus allows to identify the number of chemically significant species in the studied process. For the data in Fig. 4a , the elbow is localized around the third and fourth PC, pointing to the existence of four chemical species. However, a detailed analysis of PCs intensity vs energy (Fig. 4b ) shows that the fourth component (PC4) only shows very weak features if compared to PC3, suggesting that PC4 is a minor species. Neglecting PC4 in the description of the global XANES series the %R factor value is 0. 4%, indicating an optimal reproducibility of the dataset with three PCs only.
This spectral feature is absent in the Principal Component spectra for PC2 and PC3, which therefore both correspond to a Cu I species. In line with the smooth decrease in the scree plot between the third and fourth component (Fig. 5a ), we believe that PC1 should be connected with a pool of structurally similar mobile Cu II amino-complexes, globally accountable as [Cu II (NH 3 ) 3 (X)] + , where X = OH -, O -or NO 3 -. The simultaneous presence of multiple Cu II species, spectroscopically indistinguishable within the energy-resolution of the available (conventional) XANES dataset and inherently merged in The PC intensity was arbitrarily multiplied for the indicated factor for easier comparison the PC1 contribution, is in agreement with the observation of multiple reduction events in NO-TPR (Fig.
However, the reduction event around 190 °C, as detected by XANES, is not resolved in the NO-TPR. The quantity of Cu II reduced at high temperature is around 49% according to the NO consumption  [38]. The interpretation of the NO consumption is that the peak at 130 °C is related to a Cu II -oxide or hydroxide, while the one at 220-240 °C is related to a Cu nitratelike species, according to Eqs. (  2 )-(  4 ). From our XANES analysis, it follows that all Cu II moieties are solvated by NH 3 as [Cu II (NH 3 ) 3 (X)] + complexes, where X stands for OH -, O -or NO 3 -, and therefore mobile. All these complexes have a pseudosquare planar geometry, resulting in very similar Cu K-edge signatures in XANES. Although a direct spectral discrimination among the Cu II species is not feasible within the energy resolution of the available dataset, they can be effectively resolved through the detection of multiple reduction events, once the Cu I speciation is properly determined by MCR analysis.
Multivariate curve resolution (MCR) and principal component analysis (PCA) methods were applied to the whole dataset of XANES measured in the three experiments, to determine the number of species involved in the process, as well as their respective XANES spectra and concentration profiles as a function of temperature. The results point to the presence of mixed ligand ammonia solvated complexes at the beginning of the experiment, described as [Cu II (NH 3 ) 3 (X)] + , where X = OH -/ O -or NO 3 -. These are transformed into mobile [Cu I (NH 3 ) 2 ] + complexes, which gradually lose an ammonia ligand and become framework-coordinated Z[Cu I (NH 3 )] approximately above 200 °C. Although direct spectral discrimination among [Cu II (NH 3 ) 3 (OH)] + / [Cu II (NH 3 ) 3 (O)] + and [Cu II (NH 3 ) 3 (NO 3 )] + species is not feasible within the energy resolution of the available dataset, they can be effectively resolved through the detection of multiple reduction events, once the Cu I speciation is properly determined by MCR analysis.
Acknowledgments The authors would like to thank  H. -P. Schönherr ,  C. Hermann , and  C. Stemmler  for their dedicated maintenance of the MBE system, as well as  A. Riedel ,  W. Seidel ,  S, Rauwerdink , and  A. Tahraoui  for technical support. Furthermore, the authors appreciate the critical reading of the manuscript by  Yukihiko Takagaki. They also acknowledge the provision of beamtime under the project  HC-4068  at the  European Synchrotron Radiation Facility (ESRF) , located in Grenoble (France). ICN2 researchers acknowledge support from the  European Union   Horizon 2020 research and innovation programme  under Grant Agreement No. 881603  ( Graphene Flagship ).
The electrical resistance changes (∆R/R0) of each sensor yarns were measured with a data acquisition system (National Instruments USB-6003) simultaneously on a tensile bench MTS Criterion. The real-time electrical resistance under a loading-unloading mechanical cycle was recorded online by a computer connected to a DAQExpress Processing Software synchronously and simultaneously. All the tests were performed at a strain rate speed equal to 200 mm•min -1 and different strain values up to strain at break. The electromechanical response of the sensor yarn is quantitatively represented by the gauge factor (GF). This later can be obtained from the linear slope between the relative electrical resistance (∆R/R 0 ) and the mechanical strain (ε), according to Equation (2): ∆R R 0 = GF × ε (2).
S14-S15 ). Since an intense peak around 400-500 cm -1 is characteristic of S-S stretching mode  26  , these Raman spectra support the formation of La 2 O 2 S 1. 5 through the partial cleavage of S-S bonds. To solve the crystal structure of this novel phase, we analyzed it by precession electron diffraction tomography (PEDT) (Fig. 4a , see Fig. S16  and Table. S4 for details)  27, 28. This emerging technique allows the solution of complex structures using single nanocrystals. PEDT data were collected on several nanocrystals of the novel phase. All data sets were analyzed using the computer programs PETS2. 0 29 , Superflip  30  , and Jana2006  31. Figure  4a  shows the reconstruction of the reciprocal lattice planes hk0, h0l, and 0kl which are consistent with an orthorhombic unit cell a = 8.
The plateau temperature was maintained for 2 or 4 h before gradual cooling at RT for Ni and Ag, respectively (see Fig. 3c  for XRD). Repeated thermal treatments did not lead to further consumption of La 2 O 2 S 2 even when excess Ag was added (i. e. , using 1. 1 equiv. of Ag). In the same way, when using Ni prolonged and repeated thermal treatments did not improve the yield of oA-La 2 O 2 S 1. 5. Characterizations. Powder X-ray diffraction (XRD) patterns were recorded at room temperature on a Bruker D8 Advance Diffractometer (Bragg-Brentano geometry, θ-2θ), which employs Cu K α1 radiation (λ = 1. 540598 Å) produced through Ge (111) monochromator and a LynxEye detector. Rietveld refinements of these XRD patterns were performed with Jana2006 package  31  using the fundamental parameter approach  34.
Z-contrast imaging was performed on a Csprobe corrected STEM Themis Z G3 (Thermo Fisher Schientific) equipped with a High Angle annular Dark Field (HAADF) detector (Fischione) operating at 80 or 300 kV accelerating voltage, with a 21. 4 mrad convergence angle and 63-200 mrad collection angle. It is equipped with the 4-SDD detectors Super-X system allowing EDS analysis. Simulated images were obtained using the Dr Probe program  36. Precession Electron Diffraction Tomography (PEDT) of oA-La 2 O 2 S 1. 5. The black powder from the reaction of La 2 O 2 S 2 with Ni (vide supra) was crushed in ethanol. A drop of the suspension was deposited and dried on a gold grid with a thin film of holey amorphous carbon. 3D electron diffraction data (3D ED)  15  were collected using the precession electron diffraction tomography (PEDT) technic on a Philips CM120 electron transmission microscope (TEM) (V acc = 120 kV, LaB 6 ) with the precession device Nanomegas Digistar and a side-mounted CCD camera Olympus Veleta with 14 bit dynamic range.
USPEX is developed by the A. R. Oganov laboratory since 2004 and its detail is described in the articles from his group  13, 14. In this work, this EA code was interfaced with VASP (Vienna Ab initio Simulation Package) for DFT structure relaxation (shape, volume, atomic positions are optimized by VASP). The EA development allows the prediction of stable and metastable structures knowing only the chemical composition, i. e. , 2 La and 2 O and 1 S here, to search 3D La 2 O 2 S bulk phases. An initial population of 80 randomly created structures was considered as the first generation. Then the structures considered as worst were discarded. A structure was considered bad according to its fitness, that was the computed free enthalpy derived from ab initio total energy calculations (VASP). The remaining structures form the parent structures participated in producing the next generation.
A new candidate structure was produced from parent structures using one of four operators: (i) heredity (50%), (ii) permutation (10%), (iii) lattice mutations (10%), and (iv) soft mutation (10%). 80% of the new candidates were generated from evolutionary operators, while 20% were produced randomly. We verified that our results were not sensitive to these parameters (initial population size, ratio between the four operators), by performing multiple runs with them varying from 10% around the nominal value indicated here. The USPEX search was terminated when the global structure minimum was found in the last 10 generations. Each USPEX job was run at least twice to ensure the convergence to a global minimum. As mentioned above, structure relaxations and energy calculations were done by the external code VASP (5 INCAR files, 5 steps per phase).