dataesr/scientific-paragraphs-categorization huggingface dataset:
44 The XANES and EXAFS spectra were obtained after performing standard procedures for pre-edge subtraction, normalization, polynomial removal, and wavevector conversion. EXAFS Curve Fitting. EXAFS data were analyzed using the Demeter package, a graphical interface to the AUTOBK and IFEFFIT code. 45 First-shell analyses were conducted within a k range of 3. 0-11 Å -1 with a Hanning window (dk = 1) and an R range of 1. 0-2. 2 Å using a single Zn-O scattering path calculated with FEFF  46  using the ZnO crystal structure. 47 The parametrization of the fit was as follows: a single shift of energy was used, amplitudes were adjusted by a single amplitude reduction factor (S 0 2 ), the variation of distances for each scattering paths was adjusted by a single ΔR parameter, and the disorder was fitted with one mean relative square displacement parameter.
The FDMNES code features monoelectronic calculations, which were carried out in real space with a Hedin-Lundqvist exchange-correlation potential and using clusters built around each nonequivalent absorbing atom. Standard crystal structures (retrieved from the "Inorganic Crystal Structure Database", FIZ Karlsruhe) were used as inputs. The finite-difference method (FDM) implemented in the FDMNES code was used, since the latter is a full-potential method that introduces no approximation on the shape of the potential, which is particularly important in dealing with highly distorted structures. 51 The current implementation at KAUST of the most recent FDMNES version with the MUMPS solver allows FDM calculations with a 7 Å cluster radius, which was not possible when the built-in solver was used because of the required memory footprint and the CPU runtime.
007 and 0. 009 Å 2 (all in good agreement with the previous first-shell analysis; Table  S2 ). Next, small peaks in the FT-EXAFS spectra are due to a superposition of contributions from more distant atoms and multiple scattering effects. Examination of the corresponding RDF shows huge differences between the best structural models if we consider only the 2-4 Å range. The RDFs above 2 Å are nothing alike, which is absolutely expected, since among the five structural models selected by RMC/EA simulations (Figure  S25 ) two of them are Zn 2+ cations that are tricoordinated to framework oxygen atoms and three of them are Zn m O m (m = 3, 6, 9) clusters located in the 12-ring pore channel of the beta zeolite. In conclusion, these results serve as a compelling reminder that the same EXAFS data can be interpreted with both isolated Zn 2+ cations and disordered ZnO clusters.
Research Approach and Key Parameters In order to keep this numerical study well organised, the procedure can be summarised in Figure  2. First, the validation of this model is performed based on the experimental data of 2000 rpm-10 bar BMEP under CAC mode. Second, as nitrogen is replaced by CO2, engine operation converts into the OFC mode with nitrogen replaced by CO2, a comparison in performance between CAC and OFC is presented. Finally, the effects of WI mass, WI timing and WI temperature on OFC characteristics are explored and analysed in turn.
Research Approach and Key Parameters In order to keep this numerical study well organised, the procedure can be summarised in Figure  2. First, the validation of this model is performed based on the experimental data of 2000 rpm-10 bar BMEP under CAC mode. Second, as nitrogen is replaced by CO 2 , engine operation converts into the OFC mode with nitrogen replaced by CO 2 , a comparison in performance between CAC and OFC is presented. Finally, the effects of WI mass, WI timing and WI temperature on OFC characteristics are explored and analysed in turn. In order to increase the efficiency of water utilisation for optimising OFC process, it is usually injected directly into the engine chamber by a separated injector  [17] [18] [19] [20] [21]. Figure  3  shows the schematic of two representatives.
Engine and Testbed The model of numerical study is set up based on a practical turbocharged dualinjection SI engine fuelled with gasoline. The engine specifications and testbed overview are presented in Table  2  and Figure  4 , respectively. The used fuel of this study is commercial gasoline, which physical and chemical parameters are shown in Table  3. Regarding the data collection and analysis of the test, cylinder pressure is measured and analysed by sparkplug type piezo-electric sensors (AVL-GH13Z), a crank sensor (Kistler 2614CK1), a charge amplifier (Kistler 5018A) and a combustion analyser (AVL 641). The pressure data are recorded and averaged by 200 consecutive cycles to ensure the accuracy of measurements. A direct current electrical dynamometer measures and controls the engine's speed and torque in real-time.
The effects of adding acetylene to the fuel stream on soot formation and flame properties were investigated numerically in a laminar axisymmetric coflow ethylene/air diffusion flame using the open-source flame code Co-Flame in conjunction with an elementary gas-phase chemistry scheme and detailed transport and thermodynamic database. Radiation heat transfer of the radiating gases (H 2 O, C 2 H 2 , CO, and CO 2 ) and soot was calculated using a statistical narrow-band correlated-k-based wide band model coupled with the discrete-ordinates method. The soot formation was described by the consecutive steps of soot nucleation, surface growth of soot particles via polycyclic aromatic hydrocarbons (PAHs)-soot condensation or the hydrogen abstraction acetylene addition (HACA) mechanism, and soot oxidation.
Further Characterization of Oxygenated Products To further characterize the products of the oxidation of DBE, additional analyses and data processing were performed. A DBE oxidation sample collected at 540 K was analyzed using the flow injection analysis technique (FIA). The analyses were performed using the negative APCI-HRMS parameters given in Table  S1  of the Supplementary Materials. As can be seen from the mass spectrum shown in Figure  9 , the mass range extended to m/z > 550. This observation is somewhat unexpected for the oxidation of DBE in a cool flame, whereas it would likely be less surprising if DBE had been oxidized under simulated atmospheric conditions where accretion products have been reported for a range of organics  [24]. Unfortunately, no data are available for the atmospheric oxidation of DBE to be compared to the present results.
The HPLC-Orbitrap data are only qualitative because no calibration could be done in this work. The other data obtained by GC and FTIR are quantitative because the chemical species (reactants and products) were calibrated using standards. Uncertainties on the mole fractions are of the order of 10% in GC and 15% in FTIR. HOMs are minor products (in the ppm-range); the carbon balance could not be impacted by the fact they are not quantified in this work.
Funding: This research study was funded by the  Labex CAPRYSSES  (grant number  ANR-11-LABX-0006-01 ) from the  Labex VOLTAIRE  (grant number  ANR-10-LABX-100-01 ) and from the  Région Centre-Val-de-Loire , EFRD, and  CPER  (projects PROMESTOCK and APROPOR-E). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
1-0. 2 nA. The smallest beam diameter was 0. 2 µm for point phase analysis; some glasses were analyzed using a rectangle scanning area with a width of up to 50-80 µm. The measurements results were processed by the software package INCA Energy 200. Water contents in the starting Mg 2 C 2 O 4 were measured by the Karl-Fischer titration (KFT) on an Aqua 40. 00 system with a high-temperature HT 1300 unit at IEM RAS (Chernogolovka, Russia). Detectable water weight (m W ) range: 1 µg-100 mg, reproducibility: ± 3 µg at m W 1-1000 µg, 3% at the m W > 1 mg. Platinum analyses were performed using a New Wave Research I3107 system (Fremont, CA, USA). This is a UV femtosecond laser system equipped with a Pharos HE from Light Conversions coupled with a high-resolution ICP-MS Element-XR. A 65 µm spot size was applied with 5 Hz and 3.
These particles are larger than the particles formed during the several minutes of the quenching process. 3D distribution of large particles in the albite trap from the experiment ab86 was characterized by microX-Ray computer tomography (x-Ray CMT) with resolution 1. 8 mkm (see supplementary information x-Ray_CMTab86. avi). For MCT, the SkyScan 1172 apparatus (MSU, Moscow) was used. Due to the large density contrast (21. 45 g/cm 3 Pt versus 2. 2 g/cm 3 glass) strong reflections appear in the recordings of transmission images of sample slices. The actual particles sizes were distorted and x-Ray CMT data cannot be used for a quantitative analysis. As a result, these factors lead to a large scatter in the results of local analysis using the LA-ICP-MS (see supplementary_text, Table  S2 ). The bulk ET-AAS method gives a concentration averaged over the entire volume of the trap (or part of it) that is approximately 3.
However, from the single piece ET-AAS analysis of CRT from run cor105 and SGT from run qz120 (P = 100 MPa) we get larger values of 5 and 10 ppm with corresponding solubility of 75. 3, 70. 5 ppm, respectively. And at P = 50 MPa, the results are similar: the bulk ET-AAS concentrations of SGT (run qz119) and CRT (run cor104) are 11. 6 and 5 ppm, which corresponds to solubility of 119 and 93 ppm, which is significantly higher than the solubility of 5. 2 ppm from LA-ICP-MS analysis data of AGT (run ab107). In other words, we do not find a large difference between the solubility at 200, 100 and 50 MPa estimated from the bulk analysis of SGT and CRT by the ET-AAS method. However, AGTs analyzed by local LA-ICP-MS have demonstrated a strongly decreasing solubility at lower pressures.
Reducing of CO content towards CCO buffer limit resulted in the deposition of carbon, carbonyl decomposition and growth of the relatively large Pt particles. By discarding the LA-ICP-MS data points affected by mechanical contamination of trap and large particles, we get an estimate of the solubility in fluid of about 500 ppm. The increase in solubility from 130 to 500 ppm at X CO = 0. 18-0. 19 can be explained by the effective value of n = 5 in Equation  (13). For low pressure experiments with an albite glass trap analyzed by LA-ICP-MS, n = 5. 5 is the best fit. The only value for 300 MPa was obtained with a corundum trap, the use of which often underestimates the results. However, this solubility is at least 100 ppm and is expected to be higher (see Figure  2 ).
Reducing of CO content towards CCO buffer limit resulted in the deposition of carbon, carbonyl decomposition and growth of the relatively large Pt particles. By discarding the LA-ICP-MS data points affected by mechanical contamination of trap and large particles, we get an estimate of the solubility in fluid of about 500 ppm. The increase in solubility from 130 to 500 ppm at XCO = 0. 18-0. 19 can be explained by the effective value of n = 5 in eqn. (13). For low pressure experiments with an albite glass trap analyzed by LA-ICP-MS, n = 5. 5 is the best fit. The only value for 300 MPa was obtained with a corundum trap, the.
7 at 200,000 g/mol. Meanwhile, the branching frequency increases sharply from 0. 5 LCB per 1000 units to approximately 3 LCB per 1000 units in the range of molecular weight comprised between 20,000 and 60,000 g/mol and then remains constant at 3 LCB/1000 units on the range of 60,000 and 200,000 g/mol. Values of the average viscosity branching index, average number of LCB per molecule, and LCB frequency calculated by OmniSEC software are given in Table  3. Meanwhile, the branching frequency increases sharply from 0. 5 LCB per 1000 units to approximately 3 LCB per 1000 units in the range of molecular weight comprised between 20,000 and 60,000 g/mol and then remains constant at 3 LCB/1000 units on the range of 60,000 and 200,000 g/mol. Values of the average viscosity branching index, average number of LCB per molecule, and LCB frequency calculated by OmniSEC software are given in Table  3.
η E. ε = 3η 0 η E. ε = 3η 0 ( 10 ) It is of universal practice to compare the results of elongational flow experiments (the nonlinear material viscosity function) η + E t,. ε with the linear response given by: η + E = 3 N ∑ i=1 G i λ i 1 -e -t λ i η + E = η E -3 N ∑ i=1 G i λ i e ( -t λ i ) (11) where {G i , λ i } are the previously mentioned GMM sets of parameters. In this context, if the datasets are accurately obtained, then the nonlinear response should agree with the linear one at short times and low strain rates. In addition, the deviation of the nonlinear response from the linear one (also called linear viscoelastic envelope, LVE) is used to qualify the behavior of the material under elongational flow. If the material under elongational flow exhibits a sudden rise deviating above the LVE, the melt is said to be strain hardening, which improves processability, whereas if it drops below the LVE curve, it is said to be strain softening.
Acknowledgments: The authors gratefully thank Ceisa Packaging and the French Environment and Energy Management Agency-ADEME (n • TEZ11-26) for their technical and financial support, Jean Coudane and Sylvie Hunger (Institut des Biomolécules Max Mousseron, Université de Montpellier, France) as well as Sebastien Rouzeau from Tosoh Bioscience for their help with the SEC analysis.
Experimental measurements Pressure fluctuations were measured in the injector tubes at three locations x = -54 , -81 , -133 mm upstream of the dump plane, at three angular locations around the annulus, θ k= { 1 , 2 , 3 } = { 0 • , 120 • , 240 • }. Pressure signals (from Kulite XCE-093 sensors, 1. 4286 × 10 -4 mV/Pa) were amplified (Fylde FE-579-TA) and sampled at f s = 51. 2 kHz during ∼ 60 s for each experiment. The data presented in §3 corresponds to ∼ 10 s for each run. Signals were digitised using a 24-bit DAQ system (NI model 9174). Each operating condition was tested 5 times, resulting in 175 experiments. Further to this, the transient case studied in Section 3. 2 was tested 15 times to assess repeatability. During experiments both longitudinal and azimuthal modes were observed, with the latter found to contain significant harmonics.
g. , Jafari et al. 11  derived and subsequently verified a chemical toxicity estimation model of Vibrio fischeri based on EC 50 values (EC 50 is the efficient concentration of the studied sample resulting in 50% of reduction on processes, such as growth or reproductive activity) for 187 ILs (250 experimental points) and, importantly, the authors obtained a satisfactory compliance. Nevertheless, the database necessary to achieve acceptable results must be very large. 5] [16]  In the studies mentioned above, mainly IC 50 values (IC 50 is the inhibitory concentration of the examined material causing 50% inhibition of the activity of biochemical or biological systems) were applied to estimate the IL cytotoxicity. In most cases, the authors examined ionic systems with halide anions (for example, with bromide [Br] - or chloride [Cl] -anions).
IC 50 values along with standard deviations (confidence level 0. 95) were determined using the GraphPad Prism 8 software. Each experiment was repeated three times in triplicate (for each IL). Density Measurements. The density of the tested ILs needed for the IC 50 calculations was recorded at 310. 15 K by means of a DMA 5000 M vibrating-tube densimeter (Anton Paar, Austria). The apparatus was calibrated (an extended-temperature calibration procedure was used) with redistilled water and dried air. Importantly, viscosity correction was made automatically. The uncertainty of the listed density values in Table  2 , in each case, did not exceed ±0. 1 kg• m -3. The uncertainty in the density was evaluated using the following ref 24, in which the impact of the impurities on the uncertainty was taken into account.
Force-fields and simulation parameters Both MD and GCMC simulations were carried out using the gmq parallel package  [52]. The total molecular potential energy U pot is obtained from the sum of the angle-bending, torsional, out-of-plane, van der Waals and electrostatic interactions (Eq. (  1 )): U pot = ∑ θ U bend (θ) + ∑ τ U tors (τ) + ∑ i-planar U oop (i) + ∑ (i,j)nb U vdw (r) + ∑ (i,j)nb U coul (r) (1) Each term in Eq. (  1 ) is detailed in the Supporting Information, along with the force-field parameters for all OAPS-based molecules (Tables S1-S2-S3 and Fig. S1 ) and the cutoffs for non-bonded interactions  [30]. Those for the aliphatic POSS-based molecules are available in Refs. [26, 27]. The gas molecules were represented by optimized all-atom models for CH 4  [53]  and CO 2  [54]. High-frequency motions, i.
e. the bond stretching modes, the hydrogen vibrational modes and the O--C--O bending mode for CO 2 , were kept rigid using constraints  [55, 56] , in order to ensure a correct equipartition of the kinetic energy with a time step of Δt = 10 -15 s in the MD integration algorithm  [57]. The temperature T and pressure tensor P were maintained close to their required values by loose-coupling  [58, 59]. The MD simulations were run under either constant-volume NVT or controlled-pressure-tensor NPT conditions. The latter allows for the system to relax towards its equilibrium size and shape. The resistances to mechanical stresses were obtained by changing linearly the components of the required pressure tensors and recording the changes in box sizes and shapes. The average thermodynamic data were stored every 1 ps while the molecular configurations were stored every 5 ps for post-analysis.
Acknowledgments This work is part of the  MOLHYB  project financed by the  French ANR (Agence Nationale de la Recherche)  within the framework of the AAPG (Appel à Projets Générique) 2018. It had access to the  HPC resources of CCRT/CINES/IDRIS  under the allocations A007-and  A009-095053  made by  GENCI, France. The  MUST computing centre at the University Savoie Mont Blanc, France , is also acknowledged for the provision of computer time. Nicolas Charvin  is thanked for his help with the installation and maintenance of the laboratory local servers.
The pH variation was quantified by the variation of transfer charge resistance Rtc. This parameter was extracted from Nyquist plots of the impedance data using EC-Lab V11. 36 modelling software (Bio-Logic Science Instrument, France). EIS data were fitted using Z-fit with Randomize + Simplex method. Randomize was stopped on 100,000 iterations, and the fit stopped on 5000 iterations. The electrolyte used for both electrochemical characterizations of pH study was made from 0. 4 M (Mg (NO 3 ) 2 ) in 5 mM Tris(hydroxymethyl)aminomethane, TRIS). The pH was adjusted using 1M HCl solution. The pH values were controlled before and after the C(V) measurements by a pH meter (HI 98130, HANNA).
(B) (A) The electrochemical impedance spectroscopy (EIS) measurements were recorded by applying a sinusoidal potential amplitude of 25 mV and an optimized polarization potential fixed at -0. 3 V within the frequency range of 100 mHz to 100 kHz using a VMP3 Bio-Logic Science Instrument, France. The pH variation was quantified by the variation of transfer charge resistance Rtc. This parameter was extracted from Nyquist plots of the impedance data using EC-Lab V11. 36 modelling software (Bio-Logic Science Instrument, France). EIS data were fitted using Z-fit with Randomize + Simplex method. Randomize was stopped on 100,000 iterations, and the fit stopped on 5000 iterations.
However, the complexity of flow behavior and the strongly exothermic effect render it hard to design and scale-up the reactors  [11, 12]. During the experiments, a bench-scale oil-cooled reactor was used to control the temperature, and the reaction heat was negligible for very low reaction intensities  [13] [14] [15]. In the numerical work of  Liu et al. [16] , the methanation process was simulated numerically by using the open source package OpenFOAM. The isothermal flow assumption was adopted, and the energy equation was not included in their work. Although the products were predicted, the isothermal assumption was not suitable for the exothermic process. Li et al. [15]  simulated the bubbling fluidized with a mandatory assumption that the system was cooled by media with temperatures at 390 • C in order to guarantee that the outlet temperature was 400 • C.
Electrical Characterization The electrical characterization of metal coated SU-8 pillars and nanowire ISFET in wet conditions were performed by semiconductor parameter analyzer (Agilent 4156C) in Süss PM8 manual probe station. The SPA was controlled by EasyEXPERT group+ (Keysight Technologies, Santa Rosa, CA, USA) software via a GPIB interface. The valve control and electrolyte injection in pseudo-RE module were carried out by pressure system (OB1, Elveflow, Paris, France). The open circuit potential (OCP) measurements for pseudo-RE characterization were carried out by potentiostat (Palmsens2 and PSTrace, Palmsens BV, Houten, The Netherlands).
The simulated concentrations of ammonia were compared with ground measurements from Europe, North America and Southeastern Asia, as well as with satellite measurements. The satellite-constrained ammonia emissions represent global concentrations more accurately than state-of-theart emissions. Calculated fluxes in the North China Plain were seen to be more increased after 2015, which is not due to emission changes but due to changes in sulfate emissions that resulted in less ammonia neutralization and hence in larger atmospheric loads. Emissions over Europe were also twice as much as those in traditional datasets with domi-nant sources being industrial and agricultural applications. Four hot-spot regions of high ammonia emissions were seen in North America, which are characterized by high agricultural activity, such as animal breeding, animal farms and agricultural practices.
, 2006). For the calculation of ammonia's lifetime, the model ran with traditional emissions for anthropogenic, biomass burning and oceanic emission sources using emissions from ECLIPSEv5 (Evaluating the CLimate and Air Quality ImPacts of Short-livEd Pollutants), GFED4 (Global Fire Emission Dataset) and GEIA (Global Emissions InitiAtive) (hereafter called EGG)  (Bouwman et al. , 1997; Giglio et al. , 2013; Klimont et al. , 2017).
IASI ammonia The Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp-A satellite measures Earth's infrared radiation twice a day in a spectral range of 645-2760 cm -1 with an elliptical footprint with a diameter of 12 km at nadir  (Clerbaux et al. , 2009). Due to the larger thermal conditions that lead to smaller uncertainties, only morning data were used in the present assessment  (Clarisse et al. , 2010). Van Damme et al. (2018)  reported limited impact of the IASI overpasses of 4 % ± 8 % on ammonia. The 10-year dataset used here is the ANNI-NH3-v2. 1R-I product  (Van Damme et al. , 2017)  and relies on ERA-Interim ECMWF meteorological input data  (Dee et al. , 2011). The artificial neural network for IASI (ANNI) algorithm converts the hyperspectral range index to an column-integrated NH 3 value  (Whitburn et al.
, 2016a). The latter relies on the fact that the indices can be converted to a column by taking into account the spectral sensitivity to the ammonia abundance in the observed scene. The hyperspectral range indexes are derived from linear retrievals using a constant gain matrix which includes a generalized error covariance matrix  (Van Damme et al. , 2014b; Whitburn et al. , 2016a). The dataset also provides cloud coverage for each measurement  (August et al. , 2012). Only measurements with a cloud fraction be-low 10 % were processed in consistency with  Van Damme et al. (2018). Cloud coverage was not provided for all measurements until March 2010, resulting in lower data availability before that date. Van Damme et al. (2014a)  reported that IASI better measures ammonia in spring and summer months, due to the strong dependence on thermal contrast (error below 50 %).