dataesr/scientific-paragraphs-categorization huggingface dataset:
Neutron spin-echo measurements Quasi-elastic experiments were performed at the Neutron Spin-Echo (NSE) instrument IN15 at the Institut Laue Langevin (doi: 10. 5291/ILL-DATA. CRG-2632) in Grenoble at temperatures T = 353, 373, 393 and 413 K. We covered a q range of 0. 05 < q < 0. 13 Å -1 while accessing Fourier times from 0. 5 ns to almost 500 ns using a wavelength of λ = 13. 5 Å. Additional measurements on both comparable samples and "decorated" bound rubber layer were performed at the SNS-NSE instrument BL-15 of the Oak Ridge National Laboratory at a temperature T = 413K. The same range of q vectors was investigated for Fourier times ranging from 0. 05 ns to 70 ns. The data overlapped in good agreement between the two spectrometers. For all samples made of the 10/90 H/D polyisoprene blend, NSE data were corrected for incoherent background so that the intensities in the present article are coherent scattering.
Rheology All samples were measured in Goodyear facilities on an Anton Paar 302 rheometer using a pre-existing measurement protocol (8 mm plate-plate geometry, 1 mm gap size, convection oven temperature control with N 2 atmosphere). Applying the Time-Temperature Superposition principle (TTS), rheological master curves were built at a reference temperature (T ref = 213 K) by allowing a simultaneous horizontal (i. e. , frequency) shift of both elastic and viscous moduli (G′ and G″ respectively) measured between 0. 3 and 100 rad/s at various temperatures ranging from 203 to 353 K and an applied stain of 0. 1% for unfilled samples and 0. 03% for filled samples. The superposition procedure was achieved numerically with help of the NLREG Software from Freiburg Materials Research Center. When needed, the rheological master curves were shifted to T = 413 K by fitting and extrapolating the numerically determined log a T values with the WLF equation.
In our experimental conditions, the NSE experiments allow measuring the coherent intermediate scattering function (ISF) S(q,t)/ S(q,0) of the dilute hydrogenous polyisoprene chains within their deuterated analogues. In this way, we measured the average dynamics of chains, either belonging to the bulk or being in more restricted configurations in the vicinity of filler surface. Such a measurement is displayed in Figure  5A  where the ISFs of the neat polymer blend at different scattering are plotted. A comparison of the Fourier times accessible by NSE with the rheological master curves plotted in Figure  1  shows that the dynamics probed in the studied NSE configuration lies in the semi-flexible regime of the polyisoprene chains (between τ 0 and τ e ). In literature, NSE data of polymer blends and nanocomposites have been studied through two main models that are the Free Rouse model  [39]  and the Tube-Reptation model  [16].
The dynamic structure factor does not fully level off into expected plateaus due to the constraints that other chains cause. The fitting of NSE data was performed by using DATREAT, a software developed internally at the Jülich Centre for Neutron Science. The dynamic structure factor of the neat polymer blend was measured at four different temperatures and eight scattering vectors. For clarity, only the data gathered at 413 K are displayed on Figure  5A. The model only takes parameters that are related to the chemical nature of the polymer so that the same set of parameters must allow fitting all the ISFs obtained with this polymer. Only a time scaling parameter, t scale , can vary to account for the change in temperature between the different sets of data. Note that this parameter is strictly analogous to the log (a T ) function derived from the WLF approach.
Acknowledgments A portion of this research used resources at the  Spallation Neutron Source , a  DOE Office of Science User Facility  operated by the  Oak Ridge National Laboratory. Authors would like to thank  ORNL ,  ILL  and  JCNS  for providing them with precious beam time on SANS and Spin-echo instruments. We also thank  Sylvain Prevost  of the  ILL  for complementary SANS measurements. We thank  Evonik  for the supply of the Coupsil particles used in this study.
Acknowledgements The authors acknowledge the support of  SingFlows project , grant  ANR-18-CE40-0027  of the  French National Research Agency (ANR). D. G-V acknowledges the support of the  Institut Universitaire de France. A. M acknowledges the funding from the  European Research Council (ERC)  under the European Unions  Horizon 2020 research and innovation program  Grant agreement No  637653 , project  BLOC Mathematical Study of Boundary Layers in Oceanic Motion.
Biological Test The biocompatibility of the different biomaterials was assessed by comparing the viability of C2C12 myogenic cells after 5 days of culture (Figure  9 ). This luminescent cell viability assay is based on ATP content, a required co-factor of luciferase reaction. The luminescence produced is, thus, proportional to the amount of ATP present reflecting cellular metabolic activity. Luminescence intensity (Relative Luminescence Units) was significantly increased when cells were cultured on PHOU 20 PEGDA 80 biomaterial compared to PEGDA 100 , PHOU 50 PEGDA 50 and PHOU 80 PEGDA 20 biomaterials. In addition, similar luminescence intensity was obtained when cells were amplified on PEGDA 100 , PEGDA 50 or PHOU 80 PEGDA 20. These data showed that after 5 days of culture, a higher number of viable cells were present on PHOU 20 PEGDA 80 biomaterial than on PEGDA 100 or on biomaterials containing higher proportions of PHA (i.
This comparison choice was preferred to a simple comparison to the literature because the literature samples are not tested in the same conditions, and generally, are not embedded in commercial cases for test under gas. The commercial sensors, i. e. , MQ136 and TGS2602, from Zhengzhou Winsen Electronics Technology Co. (Zhengzhou, China), and Figaro USA Inc. (Arlington Heights, IL, USA), respectively, were tested by respecting the polarization conditions defined by the manufacturer. Additionally, for experimental measurements, data from technical datasheets were added as well, plotted in Figure  13. In these datasheets, the sensitivity is given by the relation: S = R/R 0 ( 3 ) where R is the measured resistance of the sensor under the test gas, R 0 is the resistance in the initial conditions (under air, measurement temperature).
Acknowledgments: This study was supported by the  French Research Agency (ANR Ospégaz-ANR   11ECOT 01201-OSPEGAZ  (oxydes sans plomb pour la détection de gaz). The scanning electron microscopy was performed in ScanMAT UMS 20001  CNRS-University of Rennes 1 , which received a financial support from the  Région Bretagne , the  Département d'Ile et Vilaine  and the  European Union  (2015-2020 CPER projects SCANMAT and Verres). We also would like to thank  Nicolas Uschanoff  for his help during the measurements under gas conducted at Simtronics SAS.
ACKNOWLEDGMENT This work was supported by the  Slovenian Research Agency ARRS , Grant No. P1-0208 ,  Z1-2635 ,  J1-1717 ,  Centre National de la Recherche Scientifique CNRS, Normandy University, French-Slovenian bilateral  grant  BI-FR/22-23-PROTEUS-004 , and  Los Alamos Laboratory Directed Research and Development. M. S. acknowledges Anamarija Zega  as her PhD supervisor. M. L. gratefully acknowledges the funding by the  European Research Council  ( 950625 ). T. T. acknowledges  OpenEye Scientific Software ,  Santa Fe , NM. , for free academic licenses for the use of their software. Maja Frelih  is acknowledged for acquisition of HRMS spectra.
In this work, new experimental data are generated over a wider range of experimental conditions for the O3-assisted oxidation of C2H4 to confront the predictions of current kinetic models. Especially, due to a different experimental configuration, the newly obtained data shows that a global ozonolysis mechanism can accurately simulate the mole fractions of the main products as well as the consumption of C2H4 and O3. The O3-assisted oxidation of C2H4 was carried out in a JSR between 300 K and 1000 K with varying the mole fraction of O3 from 1000 to 2000 ppm. The identification and the quantification of the main products and stable intermediates were performed by gas chromatography with mass spectrometry, thermal conductivity and flame ionization detections, and the obtained mole fractions were recorded as a function of temperature.
KINETIC MODEL An up-to-date kinetic model developed at Princeton coupling an ethylene oxidation mechanism and an O3 sub-mechanism was used to simulate the experimental data  [42] [43] [44]. Based on IUPAC recommendation (https://iupac. org/), the following direct reactions between O3 and C2H4 were implemented to simulate global ozonolysis reactions: O3 + C2H4 ↔ CH2O + OH + HCO (1) O3 + C2H4 ↔ CH2O + CO + H2O (2) O3 + C2H4 ↔ CH2O + H + H + CO2 (3) O3 + C2H4 ↔ CH2O + CO2 + H2 (4) Using the CHEMKINPro software  [47] , the oxidation of C2H4 without O3 was modelled considering a perfectly stirred reactor (see results in FIGURE  S1  in Supplementary Material) as it is usually the case when modelling JSR, since the residence time in the preheating zone is only a few percent of that in the JSR  [48].
Nonetheless CH2O, which is an important atmospheric pollutant, is the main product of the low-temperature ozonolysis reaction with a significant mole fraction ~1000 ppm. This quantitative result is important to consider especially for closed environments such as warehouses or fruit stores, where non-negligible amounts of C2H4 can be present  [54]. If these places use air purifiers, a phenomenon that is growing lately because of COVID-19, then a significant amount of formaldehyde can be expected, as many indoor appliances have been shown to generate significant amounts of O3  [55]. More generally, the quantification of oxidation products and stable intermediates under conditions relevant to atmospheric and combustion studies provides a database of temperature-dependent products that can be used as a valuable guidance for future validation and improvement of detailed chemical kinetic models.
32, 54 MATERIALS AND METHODS Details on the synthesis of the ionic liquids and corresponding analytical data are given in the Supporting Information. Halide residues in the ionic liquids could not be detected by ion chromatography. Details regarding the temperature-dependence of the macroscopic properties (experimental values of density, viscosity, and conductivity and fitting data) and the molecular dynamics simulations can also be found in the Supporting Information. Physicochemical Properties. The physicochemical properties were determined as reported in the literature. 24, 55 Prior to each measurement the samples were dried for at least 2 days in high vacuum and further stored and handled using Schlenk techniques or a Labmaster 130 glovebox (MBraun, Garching, Germany). The viscosity η was determined using a MCR 301 Rheometer (Anton Paar, Graz, Austria) equipped with an CP50-1 cone of 49.
95 mm diameter and cone angle 1°using 0. 101 mm gap size. For each temperature 30 shear rates ranging from 5 to 80 s -1 were recorded in linear steps (averaging data values over 15 s per shear rate) after sufficiently long temperature equilibration. The liquids were characterized by Newtonian behavior. The conductivity was measured using a commercial conductivity probe consisting of two rectangular platinized platinum electrodes fused in glass with a nominal cell constant of 0. 5 cm -1 (WTW, Weilheim, Germany) and a SP-150 potentiostat (BioLogic, Seysinnet-Pariset, France). The actual cell constant was determined using commercial conductivity standards. Impedance measurements were conducted at each temperature controlled by a Proline RP 1845 thermostat using amplitudes of 5, 10, and 15 mV and 50 different frequencies ranging from 200 kHz to 1 Hz in logarithmic steps.
All NMRD profiles were fitted in Matlab with the lsqcurvef it function which utilizes a nonlinear least-squares solver in combination with a trust-region-reflective algorithm. The upper and lower bounds of the fitting parameters were chosen to cover the maximum range of physically sensible values. To test for numerical stability, the starting values of the fitting parameters were randomly changed in the interval defined by the lower and upper bounds. To ensure a high numerical stability, the number of fitting parameters was reduced to a minimum. This means that only the correlation times τ trans and τ rot were obtained via fits of the experimental FFC dispersion curves. The intra-and intermolecular spin distances b and d were obtained from the MD simulations (table  S23 ) as outlined earlier and used as fixed parameters in the fitting of the FFC dispersion curves to ensure numerical stability.
However, modeling of the FFC data showed that  19  F relaxation contribution is negligible. The FFC data for all ionic liquids, with both anions, could be well-fit with the models used. The cations in this work were chosen to have similar sizes and masses, and the variations were alkyl/ether and long/short side chains. All ionic liquids were subject to comprehensive physicochemical characterization. Critically, ether functionalization was found to significantly and consistently lower viscosities, which is a key property of ionic liquids. The FFC measurements and physicochemical characterization was complemented with systematical molecular dynamics simulations. We carried out both nonpolarizable The Journal of Physical Chemistry B and polarizable simulations allowing for relative and absolute predictions, respectively.
Typically, this equilibrium is reached within 8 to 12 h. In this work, the resonance frequency f R is measured once in a minute. This is sufficient to monitor the dynamic of the water uptake by the SPEEK films. For samples with higher activity than SPEEK, the repetition rate of the frequency measurement can be further reduced to only a few seconds. The equilibrated state is identified for each RH level and evaluated by calculating the average for f R and RH in this region. As an example, the corresponding data range for the humidity step at RH = 20 % is depicted in Fig. 7. The relative humidity can be set with a precision of about ±0. 15 %. The precision of the f R determination is f ± 3. 0 Hz over the 4 h of measurement time observed. Considering Eq. (  8 ), this equals a mass resolution R m of  As described before, the resonance frequency change is converted to a mass change.
Acknowledgements. In addition, the authors thank the  Research Center Energy Storage Technologies (Forschungszentrum Energiespeichertechnologien)  for supporting this work. Financial support. The authors were financially supported by the  DFG  (grant nos. FR 1301/35-01  and  FR 1301/20-02 ). This open-access publication was funded by  Clausthal University of Technology. Review statement. This paper was edited by  Bernhard Jakoby  and reviewed by two anonymous referees.
II. 3 Differential scanning calorimetry (DSC) DSC measurements were carried out using a Mettler Toledo DSC1 STARe instrument and data were processed with STARe software. Heating/cooling rate are 10°C/min in the range -150°C to 100°C and 5 minutes isotherms are used between the different sequence. Even if no variation was depicted with thermal history, the phase transition behavior temperature was determined for the second heating cycle. The rate of nitrogen flux around the DSC chamber was controlled at 150 mL. min -1 and 50 mL. min -  inside the chamber. Liquid nitrogen was used to cool the samples.
II. 4 Viscosity Viscosity measurements were carried out with an ARES-G2 rheometer (TA Instruments), using a cone and plate geometry (diameter 40 mm, angle between cone and plate 1-2 degrees). In order to avoid humidity, the machine was covered by a plastic glovebag and filled with dried air. The temperature was controlled by a Peltier device from -10 to 90 °C. The data were treated by TRIOS software.
II. 5 Ionic conductivity Ionic conductivity of electrolytes was measured by Electrochemical Impedance Spectroscopy (EIS) using an impedance meter Hewlett Packard 4192A and results were fitted by Zview software. Measurements were performed with a micro conductivity cell on a wide frequency range 10mHz to 1MHz between -10°C and 90°C. The samples were prepared in a glovebox and PTFE tap was used to ensure an anhydrous environment. The cell constant was determined from the conductance of a reference 0. 1 M KCl solution.
II. 7 Infrared spectroscopy. Fourier transform infrared (FTIR) analyses were carried out using an IR spectrometer Spectrum ONE (Perkin Elmer). The samples were analyzed in transmission in wavenumber range between 4000 and 400 cm -1. The IR spectra were acquired with 16 accumulations and a resolution of 1 cm -1. Ionic liquid electrolytes were placed in a liquid cell with ZnSe window and measurements were performed in N2 atmosphere. Experimental data have been processed in using Origin software, and spectra are deconvoluted with gaussian shaped peaks to extract relative area of the different vibrations.
The samples were introduced into 0. 3 mmdiameter Lindemann capillaries. Samples were rotated along their longitudinal axes during data collection to minimize the effects of preferred orientations. X-Ray patterns were obtained isothermally Angles h pos and u pos describe the position of any molecule relative to a reference molecule (with darker chlorides in the figure) using the vector $ v CM that joins their centers of masses. Axis definition is the same as in our previous study on the liquid phase in order to ease comparison  [20]. between 346 K and 375 K. Acquisition times were at least 60 min, and a stabilization time of at least 5 min at each temperature before data acquisition was selected.
Neutron and X-ray diffraction on the plastic phase of hexachloroethane In this section, we will focus on the comparison of MD simulations with X-ray and neutron diffraction experiments. First, we have calculated the experimental lattice parameter as a function of the temperature coming from X-ray diffraction, within the stability range of the plastic BCC phase of C 2 Cl 6 (344-457 K), and we have compared it with the equilibrium configurations of the simulation in a NPT ensemble. The lattice parameter temperature dependence is compared to previous powder neutron diffraction data reported by Gerlach et al. [12]  and a previous simulation of Criado and Muñoz  [8]  (see Fig. 3 ). Our MD results agree with the experimental data, and fit better than the results of Criado and Muñoz  [8]. This shows that the force field and intramolecular structure used in this work reproduces better the density and thermal expansion of the crystal lattice than that of previous works.
Acknowledgments A. H. would like to acknowledge the funding by the  FPUUPC grant  from  Universitat Politècnica de Catalunya  and partial support provided by '' Departamento Adminsitrativo de Ciencia Tecnologia e Innovacion -Colciencias" from Colombia through the program  ''Doctorados en el exterior -2014". L. C. P. acknowledges financial support from the  Spanish AEI/MCIN  through project  PID2020-112975GB-I00  and the  Catalan Government  (Grant  2017SGR-42 ). D. A-G was financially supported by  Minciencias  and the  Sistema General de Regalias SGR  through Project  BPIN 20200001003467. Autors A. H. and L. C. P. would like to acknowledge inspirational conversations with  M. Periné.
Synthesis of amide bond: access to amides, peptides, and carbamates Amide is one of the most common functional groups (FG) encountered in nature as it plays a critical role in the structure and properties of the "molecules of life," such as peptides and proteins. This moiety is the most frequently encountered FG in bioactive molecules developed for pharmaceutical and agrochemical applications. A survey published in 2006 highlighted that throughout the synthesis of 128 drug candidates, the occurrence of N-acylation reactions to produce amide bonds was found to be 66% (i. e. , 84/124). 27  In 1999, an analysis of the Comprehensive Medicinal Chemistry (CMC) database based on drug-like compounds underlined that the carboxamide functional group represented up to 27% of the bioactive molecules referenced.
The choice of Δt results from a compromise. It must be small enough compared to τ α so that we can resolve how the structural relaxation unfolds from early times, but not too small so the fraction of mobile particles within each time interval is nonvanishing. With our choice, about 5% of the particles are mobile in each slice. Only particles that are mobile with a time slice are rendered. To ease visualization, we show only particles with 0 < x < L=2. We highlight the main features of the space-time trajectory by constructing a surface representation of the set of mobile particles, as implemented in the OVITO software  [81]. The most striking novel observation deduced from Fig. 16  is the emergence of "tubes" in space-time. Physically, this corresponds to localized regions in space which keep relaxing in many successive time slices.
ACKNOWLEDGMENTS We would like to thank  Jean-Philippe Bouchaud  for his support, questions, and constant interest over the last two years. Many members of the Simons Collaboration "Cracking the glass problem" have challenged our numerical results and interpretations over the last two years, which helped us improve our manuscript. We thank  G. Jung ,  D. S. Simmons , and  P. G. Wolynes  for comments on our manuscript. This work is supported by a grant from the  Simons Foundation  (Grant No. 454933 , L. B. ) and the  European Research Council  under the  EU's Horizon 2020 Program , Grant No. 740269. C. S. acknowledges support from the  Fondation l'Oréal for a L'Oréal-UNESCO for Women in Science Fellowship , a  Herchel Smith Fellowship ,  University of Cambridge , and a  Ramon Jenkins Research Fellowship  from  Sidney Sussex College, Cambridge.
Acknowledgments The authors would like to thank the  CNRS  through the  Project research PICS: No. 286849 "NanoCat " and greatly acknowledge the financial support from the  CCIFER -ANCS  and the  French Embassy  (PhD fellowship awarded to  S. Troncéa  who won the competition  « Graine de Chercheur  et  Energie Durable »). Chevreul Institute  ( FR 2638 ),  Ministère de l'Enseignement Supérieur et de la Recherche ,  Région Nord -Pas de Calais  and  FEDER  ( Fonds Européens de DEveloppement Régional ) are acknowledged for supporting and funding partially this work.
Acknowledgement: This work was partially supported by  Qatar Carbonates and Carbon Storage Research Centre (QCCSRC). QCCSRC was funded jointly by  Qatar Petroleum, Shell , and the  Qatar Science & Technology Park. Some of the computer time used for this study was provided by the computing facilities of the  Université de Bordeaux (MCIA)  and the  Université de Pau et des Pays de l'Adour.
■ METHODS Materials. The refrigerant gases R-134a, R-1234ze(E), and R-1234yf were purchased from Gas Servei, S. A. (Spain) with a purity of 99. 9 vol % and used as received. The ILs [C n C 1 im][tcm] (n = 2,4,6,8) were purchased from IoLiTec (Germany) with a purity of 98 wt % and vacuum dried to remove any traces of water. The final water content was measured to be lower than 50 ppm using the Karl Fischer coulometric method. Experimental Apparatus and Procedure. The solubility of Fgases in ILs was measured using the isochoric saturation in the same equipment described and validated in our previous publications  30, 31  and summarized in the Supporting Information of this article. Thermodynamic Modeling. The experimental solubility data are modeled using the nonrandom two-liquid activity-coefficient model (NRTL), which has been widely used  [30] [31] [32] [33] 45, [55] [56] [57] [58] [59]  to model the vapor-liquid equilibria (VLE) of fluorinated refrigerant gases in ILs.