dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGEMENTS This project received funding from the  European Union 's  Horizon 2020  with project n°857263 Twinnims. This work was partly financially supported by the  French National Research Agency  with  PIA EQUIPEX LEAF  ( ANR-11-EQPX-0025 ),  RENATECH  and  MicroTIP  ( ANR-15-CE08-0032-0 ) projects.
A thermodynamic combustion model developed in AVL BOOST software was used in order to evaluate the pollutant emissions, performance and efficiency parameters of a spark ignition engine Renault K7M-710 fueled with compressed natural gas, hydrogen and blends of compressed natural gas and hydrogen (hythane). Multiple research studies have concluded that for the near future hythane could be the most promising alternative fuel because it has the advantages of both its components. In our previous work the model was validated for the performance and efficiency parameters by comparison of simulation results with experimental data acquired when the engine was fueled with gasoline. In this work the model was improved and can predict the values of pollutant emissions when the engine is running with the studied alternative fuels.
Experimental setup The test-cell where experiments were performed is comprised of a control room and an engine test bench (Fig. 1 ). The engine under test was a passenger car spark ignited (SI) Dacia Logan 1. 6 K7M-710 with the technical specification presented in Table  1. Several determinations were made at a constant speed of 2000 rpm and 2 bar brake mean effective pressure (constant load). The engine was tested in a spark timing characteristic looking for the optimum spark advance for two air-fuel ratios (AFR), respectively stoichiometric mixture λ = 1 and lean mixture λ = 1. 25. The ECU reference calibration maps for spark timings and for injection durations were modified using ETAS INCA v. 7. 2. 1 software tool. For each determination, global parameters were measured using the Froude Consine Texcel V6 software.
Simulation modeling The AVL BOOST software was used to create a model for the K7M-710 engine. The model is made up of system boundaries (SB), pipes, air cleaner (CL), throttle (TH), injectors (I), cylinders (C), catalyst (CAT) and plenums (PL). Fig. 3  shows the symbolic model of the engine. In this simulation tool a set of equations are used to model the engine operation. The set of conservation equations to describe a one-dimensional pipe flow is given by the well-known 'Euler Equation System'. For modeling the combustion process, the 'Vibe 2-Zone' combustion model was used. The nitrogen oxides (NO x ) formation model implemented in AVL BOOST takes into account the reactions based on the well-known Zeldovich mechanism. The carbon monoxide (CO) formation model takes into account the reactions for the oxidation of wet CO.
25 as β s increases because the combustion takes place even further in the compression stroke where two different effects overlap (temperature increase by compression made by the piston displacement and temperature rise by the heat release by combustion). This behavior seems to be similar for both AFR but with higher values for lean mixture operation. The variation of the in-cylinder charge peak fire temperature is presented in Fig. 5 (b) and looks much more accentuated and with higher values at the stoichiometric mixture (it rises by 4. 18% at λ = 1 and only by 2. 5% at λ = 1. 25). In order to compare the values of pollutant emissions calculated using the AVL BOOST software with experimentally determined emissions, different coefficients values were adopted: Table  2  shows the values adopted for the correction coefficients for these emissions in case of conventional fuel (gasoline) use.
7 (b) the peak fire pressure ( p max ) variation versus spark timing. The relative errors for THC emissions are lower than 1% for both mixtures. Similar relative errors below 1% are for p max at λ = 1 and below 6% at λ = 1. 25 over the entire investigated domain. The duration of main combustion stage strongly affects the trend of THC emissions. The reducing of this stage causes an increase of THC emissions with β s for both mixtures. The maximum pressure increases with spark timing because the combustion process is developed more in compression for higher spark advances. In the work  [14] , a Zero-D combustion model, developed in AVL BOOST software and validated against the experimental results obtained on a spark ignition engine fueled with gasoline at stoichiometric condition was used to analyze the engine performance and emissions when pure hydrogen fuel and pure gasoline fuel operations were considered.
| Application of controlled mechanical shear in the liquid suspension For these experiments, the preparation of the sample followed the detailed description given above; this glass coverslip constituted both the sample support and one of the shearing plates. A second microscopy coverslip was placed above the deposited drop and corresponded to the second shearing plate. The perfect planarity and parallelism of these two microscopy coverslips were suitable for the application of controlled shear. This was obtained using a commercial device called RheOptiCAD  15, 16  (CAD instrument). It provided the ability (a) to move the top plate down at a constant and low speed to prevent excessive compression of the sample until a gap width of 500 μm was reached between the plates and (b) to connect each plate to a motor controlled by software that allowed straight translation.
| Effect of shear stress in the liquid suspension Controlled mechanical shear stress was employed to reduce CB agglomeration. The mechanical forces were initially applied using the RheOptiCAD module right after the deposition of the NR-CB suspension on the coverslip (t = 0) (Figure  2a ). Light transmission images recorded during the applied oscillation cycles highlight the formation and combination of irregular flocs, growing in size and quickly leading to a macroscopically visible phase-separated coagulum at the end of 10 oscillation cycles (10 min) (Figure  S4 ). On the other hand, approximately 1 h is needed to macroscopically observe phase separation without the application of shear. Such behavior is typical of a shear-induced aggregation mechanism, where the applied shear forces can increase NR-CB contact and drive the particles to overcome the interaction energy barrier.
However, while these results can be used to tune equations of state, they do not provide stringent tests of the phase compositions found in an LNG plant where a range of intermediate compounds is also present. Accordingly, in this work we investigated the VLE of the methane + propane + toluene system with the objective of investigating conditions where toluene is a minor component in both the liquid and vapour phases. Measurements of the VLE of this ternary mixture were conducted at temperatures between 213 and 298 K and pressures up to 8. 3 MPa. The measured VLE data for this ternary system were compared to results calculated with the AspenTech HYSYS Peng Robinson (PR) equation of state (EOS)  [26]. While both phases were measured and all the data obtained are reported here, the focus of the comparisons was on the ability of the EOS to correctly predict the toluene content of the vapor phase, as this relates directly to the risk of cryogenic solids formation in the MCHE and the operational performance of the scrub column.
Results and Model Comparison Measurements were completed along isochoric pathways with each apparatus: isochores 1, 2 and 3 were measured with the Cryostat VLE cell at temperatures between 213 K and 273 K. Isochores A, B, C and D were measured with the Bath VLE cell at temperatures range between 257 K and 298 K. In Tables  2  and 3  a total of 38 new dew point and 38 new bubble point VLE data for (methane + propane + toluene) ternary system are presented. The focus of the Cryostat VLE cell in particular was to investigate systems with very low toluene fractions. The maximum liquid mole fraction of toluene in those experiments was 0. 0379. For the Bath VLE cell, a wider range of toluene fractions was studied with the minimum liquid mole fraction of toluene being 0. 160. The predictions of the PR EOS implemented in HYSYS, which is frequently used throughout the oil and gas industry, particularly when simulating industrial LNG scrub columns, were tested against the new VLE data.
Conclusion New VLE data for the ternary mixture [methane + propane + toluene] have been measured at conditions relevant to the operation of LNG scrub columns. The mixture was studied over a wide range of conditions with toluene as the minor component in both the liquid and vapor phases. Measurements were conducted along different isochoric paths at temperatures between (213 and 298 K) and pressures up to 8. 3 MPa. These data provide an opportunity to test the performance of the equations of state used widely in the design and operation of different processes in the natural gas and LNG industry. The measured VLE data were compared here to results calculated with the HYSYS Peng Robinson (PR) equation of state (EOS) that is used widely in LNG industry. The amount of toluene in the vapour phase was found to be under-predicted by the HYSYS PR EOS by an average of around 77 % at lower temperatures, with the error increasing as temperature and toluene concentration decreased.
Here we considered molar van der Waals volumes resulting from the Molecular Modeling Pro software s j MMP , and molar van der Waals volumes from an empirical correlation with molar volumes based on Bondi's estimates for the van der Waals volume s j Bondi  [44]. The values used for the volumes as well as the surfaces are listed in Table  1. Somewhat surprisingly, as both methods intend to estimate the van der Waals volume, not only the absolute values differ but also the ratios between the components. This causes the entropy to differ,  according to the value of the molar volumes used, in such a way that a larger s is obtained when the difference in molar volume between the components of the mixture is larger. For the particular case at hand, this is the estimate resulting from the correlation based on Bondi's estimates  [44].
Conclusions We have shown that an ideal entropy of mixing underestimates the entropic contribution for mixtures of components often used for DESs. Accounting for volumes of the components according to Fig. 3. Diagrams for Pe 4 NBr-erythritol describing (I) the entropy of mixing, (II) the melting point depression predicted based on entropy alone (h = 0, curves) compared to experimental data (symbols), (III) the enthalpy of mixing obtained after fitting measured melting point depressions, and (IV) the fitted melting point depressions compared to experimental data. Various entropy models are used: ideal, Flory-Huggins, and Staverman-Guggenheim. The latter two are combined with van der Waals volumes and areas estimated using the Molecular Modeling Pro software (MMP) and Bondi's method. Experimental data taken from Ref.
Experimental The experimental data reported here was directly taken from our previous publications  [31, 32, 46]. Molar volumes were experimentally obtained by measuring the densities at room temperature using a Micromeritics AccuPyc II 1340 Gas pycnometer. The melting points of the different ratios of the mixtures were measured using melting point capillaries. The DES compositions used were prepared inside a glove-box with dry nitrogen atmosphere, yielding DES mixtures with moisture levels below 10 ppm. The temperature of the first liquid visible at a heating rate of 5 K • min -1 was taken for the solidus line (eutectic temperature); the temperature at which the last solids were observed to disappear at a heating of 1 K • min -1 was taken for the liquidus line (melting point). The van der Waals volumes V m and surface areas A m have been obtained following Bondi based on measured molar volumes, according to Vera et al.
Acknowledgments GdW and RT acknowledge  Gerard Krooshof  ( DSM ) for useful discussions on the thermodynamics of mixtures. The authors would like to thank  Marco Hendrix  for the experimental support provided, and the members of the  ISPT "Deep Eutectic Solvents  in the pulp and paper industry" consortium for their financial and in kind contribution. This cluster consists of the following organisations:  Altri-Celbi ,  Buckman ,  Crown Van Gelder ,  CTP ,  DS Smith Paper, ESKA, Essity, Holmen, ISPT, Mayr-Melnhof Eerbeek, Metsä Fibre, Mid Sweden University, Mondi, Omya, Parenco BV, The Navigator Company, Sappi, Essity, Smurfit Kappa, Stora Enso, Eindhoven University of Technology, University of Aveiro, University of Twente ,  UPM ,  Valmet Technologies Oy ,  Voith Paper ,  VTT Technical Research Centre of Finland Ltd, WEPA and Zellstoff Pöls.
Acknowledgement CJ thanks the Australian Research Council (postdoctoral fellowships to AP and KY) and the US Air Force Asian Office of Aerospace Research and Development (grant FA2386-18-1-0125). LM is a senior member of the Institut Universtaire de France and thanks the Humboldt Foundation and the Chinese Academy of Science. AP thanks the Alexander von Humboldt Foundation for a Feodor-Lynen Fellowship. Dr. Stephen Best (University of Melbourne) is thanked for the loan of  13  CO.
Regarding process optimization, a simple 1D simulation approach provides a global description of the process all along the screws, whereas 3D models allow a more or less accurate description of the flow field in the different full zones of the extruder. However, most of these simulations are based on simplified steady-state 1D models (e. g. , Ludovicc© software  [18] ). Actually, the main processing parameters such as residence time, temperature, and extent of the reaction are assumed homogeneously distributed in any axial cross section. The use of one-dimensional models allows significant reductions of the simulation effort (computing time savings). In any case, the flow model is coupled with reaction kinetics that impact the fluid rheology  [19]. Thus, one-dimensional models are specially appropriate when addressing optimization or control in reactive extrusion.
Acknowledgments: Authors acknowledge ESI Group by its research chair at Arts et Metiers Institute of Technology, the  French ANR  through the  DataBEST  project as well as  Nicolas Garois (Hutchinson company)  for initiating the experimental part of this project with the support of the  Total Research Department (La Defense, Paris). Mathilde Aucler ,  Aurelie Vanhille  and  Luisa Barroso-Gago  are thanked for their help with the extruder and mechanical experiments.
■ ACKNOWLEDGMENTS The  Max Planck Society  and the  European Research Council , under the European Union's  Seventh Framework Programme  (FP/2007-2013)  ERC  grant agreement no. 615414  (S. D. ) and  NFFA EU grant  ( H2020 ) no. 654360  (R. B. ), are acknowledged for funding. The PolLux end station was financed by the  German Ministerium fur Bildung und Forschung (BMBF)  through contracts  05K16WED  and  05K19WE2. The authors thank  Christian W. Lehmann  from the  Max-Planck-Institut fur Kohlenforschung  for supporting the STEM measurements.
For Pd K-edge measurements, ca. 10 mg of powder were packed in a 2. 5 mm-diameter capillary, while for Zn K-edge data collection, ca. 1 mg of catalyst was packed in a 0. 7 mmdiameter capillary. The capillary reactor was then connected to an appropriate gas-flow setup for the CO 2 hydrogenation reaction. Temperature at the measurement position was controlled by a heat gun. A total flow rate of 12 ml min -1 was employed during all the experiments, consisting of i) activation from ambient temperature to 400 °C at 1 bar in 10H 2 /2He and kept for 60 min at 400 °C, ii) cooling down to 250 °C in H 2 and flushing with He, iii) pressurizing in He to 8 bar iv) CO 2 hydrogenation reaction with 2. 5CO 2 /7. 5H 2 /2He at 250, 300, 350 °C at 60 min reaction time for each temperature. Pd K-edge and Zn K-edge XAS spectra were collected in transmission mode, using a water-cooled flat Si(111) doublecrystal monochromator.
PXRD data were collected quasi-simultaneously with XAS measurements. The patterns were recorded by CMOS-Dexela 2D detector. The sample-to-detector distance l = 419. 91 (8)  mm and photon wavelength λ = 0. 50544(2) Å, selected by a Si(111) channel-cut monochromator, were calibrated using reference LaB 6 and Si materials. The above geometry resulted in 2θ range 1. 2-35. 0 (d min = 0. 85 Å). For a given experimental condition, 5 consecutive acquisition by 10 s each were acquired and averaged. For dark field correction, dark images (with closed X-ray shutter) were collected with the same statistics and subtracted from the data. Azimuthal integration of 2D patterns was done in PyFAI code  52  to obtain IĲ2θ) data using integration parameters initially determined in Fit2D program. 53.
Acknowledgements CAS, UO: acknowledge  Research Council of Norway  for funding through grant number  288331  ( CO2LO ). EB: acknowledges the CASCADE-X  MSCA-IF  project; this project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie  grant agreement No  793423. ALB: acknowledges  Russian Science Foundation  project No. 18-73-00189  for funding the research (participation in the synchrotron experiment and data analysis). EB, SB, MT, UO: acknowledge the  COZMOS  project; This project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No. 837733. We thank  Alina Skorynina  and  Elizaveta Kamyshova  for their help during XAS and PXRD measurements.
[22]  and Saada  [23]  based on the recommendations from the review of Larachi et al. [24]. Related equations along with the validation ranges are given below. Both correlations were obtained under laminar conditions in the upflow mode of operation, conditions that match the operating conditions used during the experiments of this work. J D ¼ 1:31 Re L ð Þ À0:436 with J D ¼ k LS a LS a t 1 v SL l L q L D m 2=3 0:2 < Re L < 20 ð Þ ; ð11Þ Sh ¼ k L ad 2 p D m ¼ 10:72Re 0:22 G Re 0:32 L D p D R 0:33 4 < Re L < 105 ð Þ ; 20 < Re G < 450 ð Þ : ð12Þ Liquid axial dispersion values were computed from Belfares et al. [25]. Liquid hold-up was obtained from the correlation of Bensetiti et al. [26]  calibrated with an experimental database of 1322 points from experiments carried out in upflow. Both correlations mentioned before are not presented here as they have been directly coded within the flooded-bedsimulator developed by the Université de Laval, Canada.
Characterization techniques The obtained fibers were analyzed using scanning electron microscopes (JEOL JSM-IT100 or Philips XL30). Both were equipped with an EDX analyzer. The samples were first gold-coated using a sputter coater. The mean diameter was measured using image analysis software (Image J) from 100 fibers. X-Ray diffraction patterns were collected on a PANalytical MPD X'Pert Pro diffractometer operating with Cu Kα radiation (Kα=0. 15418 nm) equipped with an X'Celerator real-time multiple strip detector (active length=2. 12°2θ). The powder patterns were collected at 25 °C in the range 3<2θ<70, step= 0. 017°2θ, time/step=220s. The phases identification has been measured with the X'Pert High score software (PANalytical) and the PDF-4+ 2018 database from the International Centre for Diffraction Data (ICDD).
X Ray photoelectron analysis (XPS) was performed in a multi-technique system (SPECS) equipped with a dual Mg/Al X-ray source and a hemispherical PHOIBOS 150 analyzer operating in the fixed analyzer transmission (FAT) mode. The spectra were obtained with a pass energy of 30 eV, the Al Kα X-ray source (hυ = 1486. 6 eV) was operated at 200 W and 12 kV. The working pressure in the analyzing chamber was less than 2•10 -6 Pa. Casa XPS software was employed for data treatment corresponding to regions O 1s, C 1s, Sr 3d, La 3d and Ce 3d (as internal reference u''' 916. 5 eV). Peaks were considered as a mixture of Gaussian and Lorentzian functions in a 70/30 ratio.
Thermodynamic equilibrium calculations of the proposed mechanism found it to be favorable, albeit slightly less than the Toussaint-Kagan mechanism. 12 owever, these calculations omitted the formation of the intermediate 3-buten-2-ol, the expected product of a Prins reaction between acetaldehyde and ethylene. Our own calculations, made using the Aspen Plus® software with mixtures of pure components (vide infra), indicated that the intermediate product formation step is highly endergonic. Although they also proposed a Prins-like mechanism, Natta and Rigamonti rejected it after the addition of 20% ethylene to the reactant feed failed to improve the butadiene yield. Taifan et al. 100  and Zhang et al. 136  investigated the Prins-like mechanism in their DFT calculations on the conversion of ethanol, finding the formation of the new C-C bond to have a higher energy barrier than the aldol condensation on MgO and ZrO 2 , respectively.
Their results further indicate that the reaction becomes favorable above 420 K. The authors also determined the conversion of ethanol to butadiene to be endothermic by 102-109 kJ mol -1 from 473 to 773 K. In their review of the ethanol-to-butadiene reaction, Sels et al. reported the most comprehensive thermodynamic study of the reaction, which was performed with the Aspen Plus® software using pure compounds in their gaseous states for simulating the various reaction steps at different temperatures. We performed thermodynamic simulations of our own using the same approach as Sels et al. with the Aspen Plus® software to further investigate the theoretical influence of pressure on the feasibility of the reaction. Since our results coincide mostly with those of Sels et al. , we consider this section complimentary to their work and refer the reader to their article for further details.
Acknowledgements The authors acknowledge the support from the  French National Research Agency  ( ANR-15-CE07-0018-01 ). Chevreul Institute  ( FR 2638 ),  Ministère de l'Enseignement Supérieur, de la Recherche et de l'Innovation ,  Région Hauts-de-France  and  FEDER  are acknowledged for support and partial funding of this work. We thank  Dr. Lee  and  Dr. Cheong  for providing us with high-resolution TEM images.
The data obtained in the Constant volume Preburn Vessel (CPV) were compared with simulation results obtained from different soot models coupled with a large-eddy simulation for n-Dodecane combustion  [10, [15] [16] [17]  or a k-e turbulence model  [18, 19]. The simulations were validated with 15% of oxygen and various combustion products. To complete the available database and to improve modelling concepts, a parametric study on the effects of EGR composition on soot formation for ECN spray A is needed. In the present study, the New One Shot Engine (NOSE) was used as experimental set-up since the initial conditions required for ECN-spray A are attainable and the ambient mixture composition can be adjusted as desired  [20]. The experiments were conducted for Spray A conditions, i. e. 900 K and 22.
Acknowledgments. The authors acknowledge the  National Research Agency  (contract  ANR-14-CE22-0015-01 ) for financial support to the  ECN-France  project and  Region Centre Val de Loire  (CPER 2007-2013  Energies du Futur)  and  FEDER  for financial support to build the NOSE set-up. The authors thank  H. Ajrouche ,  O. Nilaphai ,  Y. Haidous , and  B. Moreau  for helping with the experiments. The authors greatly acknowledge the valuable discussions with  G. Bruneaux.
Acknowledgements CJ and LM thank the  Australian Research Council  for funding. CJ acknowledges support from the  US Air Force Asian Office of Aerospace Research and Development  (grant  FA2386-18-1-0125 ). KY acknowledges the  Science and Engineering Research Board of India  for a postdoctoral fellowship ( SB/OS/ PDF-098/2016-17 ). Part of this research was undertaken on the MX2 beamline at the  Australian Synchrotron , part of  ANSTO.