dataesr/scientific-paragraphs-categorization huggingface dataset:
As hydrogen as well as Na, I are not accessible in the recorded spectra range, the presented atomic concentrations refer to cC + cN + cO = 100 at%. To unravel variations of the local bond states within the sensor cross-sections without a priori knowledge of the resultant reaction products, principal component analysis (PCA), as implemented in GMS 3. 40 (with Varimax orthogonal matrix rotation) 54  was applied to the recorded EELS datasets. As a result, PCA components were obtained, which describe individual phases, meaning, which include all three ionization edges, rather than individual element-specific signals. The spatial distributions in the main manuscript depict the lateral weighting factors of those identified components/phases. Due to better statistics, however, the phase-specific PCA components were separated into their C, N, and O contributions (independent background correction for each ionization edge), normalized with respect to the maximal intensity of the C K ionization edge and presented throughout the manuscript.
Acknowledgements We gratefully acknowledge funding from the  Fonds der Chemischen Industrie  and the  Max Planck Society  and the support from  Prof. Markus Antonietti. Part of this work was performed at the  DFG-funded Micro-and Nanoanalytics Facility (MNaF) of the University of Siegen  ( INST 221/131-1 ) utilizing its major TEM instrument FEI Talos  F200X  ( DFG INST 221/93-1 ,  DFG INST 221/126-1 ) and sample preparation equipment. Work at the Molecular Foundry was performed at the  National Center for Electron Microscopy (NCEM) in the Molecular Foundry (MF)  at the  Lawrence Berkeley National Laboratory (LBNL)  supported by the  Office of Science, Office of Basic Energy Sciences , of the  U. S. Department of Energy  under Contract No. DE-AC02-05CH11231. The authors thank  Klaus Bienert  for help with the humidity generator and  Heinrich Horstmann  for fruitful discussions about the optimization of the cross-sectional TEM preparation.
The RSM relies on a database of 90 points obtained thanks to a Latin Hypercube Sampling (LHS) approach. Figure  4  presents the results of a validation test, comparing the predictions of the RSM for CL and CD with validation database computed at BPR = 12 and nominal nacelle location. In the targeted range of CL, around 0. 45, the predicted values are in line with the computations. The remaining tool capabilities are based on semiempirical approaches. High-fidelity results have been validated through  [6]. 3. On-board-system and SFC sensitivity. The OBS discipline named ASTRID  [7]  sizes the overall on-board-system. It is based on semiempirical and physicsbased models. Starting from the typical loads for the OBS such us hinge moments, hot/cold air required, avionics functions, and others, the single user subsystem has been designed.
The load case considers only the static load corresponding to a cruise flight condition at maximum load factor. The wing structural model is the same for all the DOE points, as that shown in Figure  6. A RSM has been developed to reduce the workflow computational time. The RSM relies on a database of 56 points obtained thanks to a Latin Hypercube Sampling (LHS) approach. This tool minimizes the wing mass by tuning lamination parameters and thicknesses while making sure aeroelastic stability, angle-of-attack, strength, and buckling constraints are satisfied. The noise competence computes the emission of noise at the certification points accordingly to the FAR36 and ICAO Annex 16  [13, 14]. It also provides the noise margin from the certification limits. Moreover, the tool is also capable to generate a noise footprint for landing and take-off on a georeferenced map, accordingly to a selected airport.
The main outputs are the drag polar for different flight conditions (take-off, climb, cruise, landing), the lift coefficient trend, also in stall condition, and the pitching moment coefficients. The tool account also for engine geometry and position, received as input. In this manner, the aerodynamic impact of different engine BPR and location is considered. A RSM has been developed to account for high fidelity results in high-speed condition, CFD analysis have been computed in cruise condition for different engine position with engine on and off, to account for both pylon and installed engine effect on drag coefficient, for the wing-body configuration (as shown in Figure3. The RSM relies on a database of 90 points obtained thanks to a Latin Hypercube Sampling (LHS) approach. Figure4presents the results of a validation test, comparing the predictions of the RSM for CL and CD with validation database computed at BPR = 12 and nominal.
In situ spectroscopy CO 2 adsorption and CO 2 methanation over the synthesized materials were probed using steady-state in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) using a Nicolet iS50 FTIR spectrometer (Thermo Scientific), equipped with a Mercury-Cadmium-Telluride (MCT) detector and a high temperature reaction chamber (Harrick Scientific). Additionally, the CO 2 methanation over the prepared materials was investigated by in situ modulation excitation phase-sensitive detection DRIFTS (ME-PSD-DRIFTS) using the same spectrometer. The ME-PSD analysis highlight the species that change with the modulation frequency (f). The collected spectra were converted into the socalled frequency domain by Fast Fourier Transform (FFT). The data was then filtered at the modulation frequency and converted into the phase-domain by Inverse Fast Fourier Transform (IFFT).
Characterization of the catalysts Our catalytic testing reveals that both Ni/CeO 2 and Ni/ACR-CeO 2 exhibit similarly excellent catalytic properties at reasonably low reaction temperatures, despite being based on different supporting materials. Therefore, we characterized the catalysts to determine the parameters that govern the methanation performance. Even though Ni/CeO 2 and Ni/ACR-CeO 2 have similar catalytic properties (Fig. 1 ), the data presented in Table  1  demonstrate that the catalysts exhibit quite different textural properties. The textural properties of the synthesized materials were estimated using Brunauer-Emmett-Teller (BET) and Barrett-Joyner-Halenda (BJH) methods. Pure CeO 2 support has a relatively low specific surface area (S BET ) of 104 m 2 g -1 , while the pure ACR support has about 7-fold higher S BET = 784 m 2 g -1.
5 cm 3 min -1 and N 2 = 100 cm 3 min -1 ). Fig. 6  shows the phase-resolved spectra of the modulation excitation in situ DRIFTS studies conducted for Ni/CeO 2 at 250, 300, and 350 • C. A comparison of Fig. 5  and Fig. show that the data from the ME-PSD-DRIFTS experiments look quite different from those of the steady state experiments. In particular, three main differences can be identified: (i) the peak detected in the steadystate spectra at 1700 cm -1 (Fig. 5b ) is actually caused by a convolution of 2 peaks that are out-of-phase during modulation (Fig. 6 ); (ii) instead of 4 peaks observed in the steady-state spectra between and 1200 cm -1 (Fig. 5b ), the phase-resolved spectra show 7 peaks (Fig. 6 ), indicating the appearance of new groups not identified in the steady-state spectra, namely, p -CO 3 and carboxylate (CO 2 δ-) groups (Table  2 ); and (iii) two from those 7 peaks are out-of-phase with the others (Fig.
Therefore, the disappearance of the band from br-CO at high temperatures is related to desorption, instead of hydrogenation to CHO. Thus, the data indicate that the br-CO does not play a significant role in the reaction pathway but may be related to the formation of the CO Scheme 1. Proposed mechanism for the CO 2 methanation over Ni/CeO 2 catalyst, displaying the formation/transformation of the reaction intermediates as elucidated by in situ ME-PSD-DRIFTS. The green boxes mark the differences in the mechanism between the two samples (Scheme 1 vs. Scheme 2). byproduct (Scheme 2 (b)). Regarding Ni catalysts supported on carbon materials, Hu et al. [17]  concluded that the methanation over Ni catalyst supported on graphene aerogel followed the formate pathway, with carbonate intermediates being present, i.
Acknowledgments L. P. L. G. thanks the  Portuguese Foundation for Science and Technology (FCT)  for the PhD grant ( SFRH/BD/128986/2017 ). This work was financially supported by  LA/P/0045/2020  ( ALiCE) ,  UIDB/50020/ 2020  and  UIDP/50020/2020  ( LSRE-LCM ), funded by  National Funds through FCT/MCTES (PIDDAC). O. S. G. P. S. acknowledges FCT funding under the  Scientific Employment Stimulus -Institutional Call  ( CEE-CINST/00049/2018 ). S. K. thank the  Independent Research Fund Denmark  (grant no. 6111-00237  and  0217-00146B ) and the  Villum Foundation  (grant no. 13158 ). Yu. V. K. thanks the  FCT  for support under the  CritMag Project  ( PTDC/NAN-MAT/28745/2017 ).
Acknowledgements Financial support was provided by  CEA  ( DRF Impulsion 2017 ),  CNRS , the  University Paris-Saclay , and the  European Research Council  ( ERC Consolidator Grant  Agreement no. 818260  (to TC) and no. 864576  (to DA)),  ANR  ( ANR-19-CE07-0046 ). The authors thank  D. -A. Buisson ,  A. Gaudet  and  S. Lebrequier  for the excellent analytical support.
Computational Methodology Geometry Optimization First, the geometry and charge density of all molecules used in this work were optimized using the TmoleX software package  [19]  using the def2-TZVPD basis set and the density function theory (DFT). Once the geometry optimization of the molecules are completed, ". cosmo" files are generated using the single point calculation before being imported to the COSMOthermX software for solvent screening. In this work, all single point calculations were performed using the BP_TZVPD_FINE_19. ctd parameterization. This parameterization is selected because it is the most accurate interpretation for calculations involving DES and IL, as it uses fine cavity, which is a novel type of molecular surface cavity construction  [20]. The molecules involved in the system, which comprises DES (HBA and HBD), solute (phenol), and carrier (model oil components, i.
Experimental Results The LLE data of ternary systems were experimentally obtained at 298. 15 K and 101 kPa bar to investigate the performance of ammonium and phosphonium-based DESs towards the extraction of phenol from model pyrolysis oil. Table  4  presents the acquired LLE data, which are visually represented as triangular ternary plots in Figure  9. The distribution coefficient values (D) obtained from the experimental LLE data may be used to further evaluate the extraction performance of both DESs and are presented in Table  4. As the composition of phenol increases in the feed, the fraction of toluene decreases in the raffinate phase. However, the concentration of phenol remaining in the raffinate phase for all feed compositions is still very small. It was also observed that the concentrations of phenol left in the raffinate phase were very minute, indicating almost quantitative extraction.
Conclusions In this work, two DESs, MTPPBr/EG and ChCl/MEA, were synthesized at a molar ratio of 1:3 and 1:5, respectively. These DESs were used for the liquid-liquid extraction of phenolic compounds from pyrolysis oil. The ability of the synthesized DESs to selectively extract phenol from model oil were demonstrated as it was possible to extract a large amount of phenol in a single extraction stage, based on the high values of distribution ratio reported from the LLE experiments. To investigate the effectiveness of ammoniumand phosphonium-based DESs in the extraction of phenol from model pyrolysis oil, LLE data of ternary systems were acquired experimentally at 298. 15 K and 101 kPa pressure. In the removal of phenol from toluene, ChCl/MEA (1:5) exhibited higher selectivity values than MTPPBr/EG (1:3).
Acknowledgements  R. C. Pullar  wishes to thank the  FCT  (( Fundação para a Ciência e a Tecnologia, Portugal ) Grant  IF/00681/2015  for supporting this work. B. A. E. Ben-Arfa  thanks  FCT  project  H2CORK (PTDC/CTM-ENE/6762/2014 ) for supporting him during this work. This work was developed within the scope of the project  CICECO-Aveiro Institute of Materials ,  UIDB/50011/2020 & UIDP/50011/2020 , financed by national funds through the  FCT/MEC  and when appropriate co-financed by  FEDER  under the  PT2020 Partnership Agreement.
Considering the phenotypic polymorphism of the series Versicolores species, the isolates were identified by molecular biology. Spore suspensions and extracts were prepared from the isolates before being submitted to a measurement of their oxidative potential and their toxicity on a respiratory cell line (A549) and a cutaneous cell line (HaCaT). The data collected were analyzed to compare the biological activities of seven species in the series Versicolores, and to determine if the oxidative potential could be a predictor of cellular toxicity.
The PCR products were then sequenced by Eurofins Genomics (Eurofins Genomics, Hamburg, Germany). The obtained sequences were compared using BLAST (Basic Local Alignment Search Tool, NCBI) to the reference sequences of the 17 Aspergillus species of the series Versicolores (accession numbers: JN853946, JN853963, JN853980, EF652264, EF652273, KJ775086, LC000552, JN854007, KU613371, EF652284, JN853979, JN853970, EF652274, EF652302, JN853976, JN854003, EF652266)  [15]. Isolate identification was considered reliable only by having a % ID ≥ 99%. All Aspergillus isolates belonging to the series Versicolores (n = 22) were grown on MEA+ and stored on slant agar at 4 • C and in a cryoprotective agent composed of sterile water and 10% glycerol (Carlo Erba, Val-de-Reuil, France) at -80 • C before any further testing.
Statistical Analyses Descriptive statistics were calculated to provide information on oxidative potential. Rates of DTT consumption by spore suspensions and fungal extracts were subjected to the Mann-Whitney test. The percentages of cell survival were subjected to the Kruskal-Wallis test. Only results at p < 0. 05 were considered statistically significant. Statistical analyses were performed using SAS system v. 9. 4 (SAS Institute Inc. Cary, NC, USA) and XLSTAT v. 2021. 2. 1. 1120 (Addinsoft, Paris, France).
This manuscript presents an updated open-source version of the Hypersonics Task-based Research (HTR) solver. The solver, whose main features are presented in Di Renzo et al. (2020) [9] and Di Renzo & Pirozzoli (2021)  [10], is designed for direct numerical simulation of reacting flows at high Reynolds numbers. This new version extends the applications of the HTR solver to turbulent combustion in the presence of external electric fields. In particular, a new distributed Poisson solver compatible with heterogeneous architectures has been incorporated in the algorithm to compute the electric potential distribution in bi-periodic configurations. The drift fluxes of the electrically charged species are now included in the transport equations using a targeted essentially non-oscillatory scheme. A verification of these new features of the solver is provided using one-dimensional burner stabilized flames, whereas a three dimensional turbulent flame is utilized to discuss the scalability of the proposed numerical tool.
Similarly, few compressible Navier-Stokes solvers have been open sourced in the past few years. For instance, STREAmS  [3]  and OpenSBLI  [4]  are finite difference solvers for ideal gas mixtures. The first solver uses CUDA Fortran to generate GPU compatible binaries, whereas, OpenSBLI is written using Python-based code generator that automatically produces CPU and GPU compatible routines. Both these applications rely on static scheduling of the data communications across the nodes based on Massage Passing Interface (MPI) libraries and have proved to be efficient and scalable. However, the difficulties and potential performance issues that can be encountered in static scheduling of the data communications among the nodes and devices are bound to increase as the complexity of the HPC system architectures and the size of the calculations increases toward exascale computing.
In particular, the Hypersonic Task-based Research (HTR) solver  [9, 10]  is a finite-difference multicomponent compressible reacting flow solver designed to compute hypersonic flows at high-enthalpies leveraging HPC systems with heterogeneous architecture. One of the innovative aspects of this solver is its implementation with the Regent programming language  [12]. This programming language is designed to efficiently produce applications compatible with the Legion programming model and takes care of automatically compiling binaries that are compatible with GPUs and CPUs. The task-based approach has many features that ease the implementation of complex applications compatible with heterogeneous architectures. Among these features, the composability of task-graphs is particularly advantageous in assembling multiphysics solvers.
In fact, task-graphs defined in various modules of a multi-physics solver can be automatically merged into a single task-graph by the Legion runtime. In this way, the runtime manages the various data structures required by each module ensuring correct synchronization of the components to preserve the correctness of the algorithm. This feature of the task-based programming model is exercised by the presented new version of the HTR solver to predict the behavior of electrified turbulent flames. The prediction of the interaction between external electric fields and hydrocarbon flames is very challenging from a numerical point of view. In fact, though this technology could lead to significant improvements in active control of combustion, there are very few numerical investigations that have studied it.
Even though significant advances in the numerical methods for the simulation of electrified flames have been accomplished  [26] , the numerical prediction of turbulent flames impinged by electric field still appears very challenging even in academic configurations. In this work, an updated version of the HTR solver is presented with the intent of providing an efficient, opensource, and scalable tool that can be used to predict the behavior of turbulent electrified flames in bi-periodic geometries like 2D and 3D temporal reacting mixing layers. The rest of the manuscript is organized as follows. Section 2 provides a description of the mathematical formulation utilized in the solver. The dimensionless formulation of the transport equations implemented in the new version of the solver is presented in Section 3.
[9]  and also proposed in this work for reference. In fact, the coupling of the newly implemented Poisson solver triggers complex data communication patters within the time-advancement algorithm of the transport equations. Two very different facilities have been utilized during these tests in order to assess the performance and portability of the solver on supercomputers with and without GPUs. Marconi 100, which is installed at the HPC center of CINECA in Italy and currently is ranked 11 th in the Top500, has been utilized to test the scalability of the solver on multi-GPU machines. In fact, four NVIDIA Volta V100 GPUs and two IBM POWER9 AC922 CPUs are installed on each node of Marconi 100. These components produce a computational power of about 32 TFlops. Conversely, the supercomputer Quartz at Lawrence Livermore National Laboratory has been utilized to test the solver in CPU-based computing architectures.
Two 18-cores Intel Xeon E5-2695 are installed on the nodes of this supercomputer. The powerful nodes of Marconi 100 allow the user to  consider setups with many more grid points per node than Quartz. For this reason, the same calculation performed on the two machines will have much less communications with larger size on Marconi 100, whereas it will use more nodes which will communicate fewer data on Quartz. These different balances between communications and local floating point operations force the runtime to apply different strategies in order to hide the overhead of data communications. It is noteworthy that the results shown in this section have been obtained by porting the exact same version of the solver on these two different supercomputers without implementing any machine specific tuning.
Fig. 6  shows the speedup achieved by the HTR solver during a strong scaling test based on the described electrified reacting mixing layer configuration. This strong scaling test is performed on Marconi 100 and Quartz by associating a computational domain composed of 256 × 64 × 256 and 128 3 points, respectively, to an increasing number of nodes. The solver shows an ideal speedup on Marconi100 up to 2 nodes (8 GPUs) for the considered computational grid in the electrified setups where the Poisson solver is deployed. At higher node counts, the reduction of floating point operations assigned to each GPU and the increase in the data communication overhead lead to a degradation of the solver performance and, eventually, to a saturation of the speedup at 8 nodes (32 GPUs). Such saturation is delayed in non-electrified conditions because of the lower data movement.
Additionally, the HTR solver has been upgraded to consider the effects of ion wind on charged species distribution. To this end, a GPU-compatible Poisson solver suitable for bi-periodic computational domains has been implemented in the software framework and interfaced with the algorithm. The new additions to the solver have been tested using onedimensional burner stabilized flames. The accuracy of the obtained solutions has been assessed by comparing it with the results of calculations performed in the open-source solver Cantera. The calculations described in this manuscript show that the HTR solver is capable of accurately predict the combustion process and the electrically charged species distribution in the flame. Moreover, the capabilities of the HTR solver to compute three dimensional turbulent flames impinged by external electric fields are shown by performing calculations of a temporal reacting mixing layer.
This setup has been used to perform scalability tests of the solver, which has shown a parallel efficiency, measured using a weak scaling test, above 93% on up to 128 GPUs and above 88% up to 64 CPU nodes. While the new capabilities of the HTR solver can be readily used by new users to investigate the behavior of turbulent flames even in the presence of external electric fields, the presented version offers a solid software base for further developments of this tool. For instance, the current implementation provides a flexible infrastructure where complex descriptions of the transport properties of the reacting species, and particularly of the charged species  [16, 39] , could be incorporated. On the other hand, future developments of the solver will certainly focus on lifting the constraints on the complexity of the geometry posed by the current numerical methods.
Acknowledgements This investigation is funded by the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No. 898458. The author acknowledges the CINECA award under the  ISCRA initiative IsB22_3dS-BLI , for the availability of high performance computing resources and support, as well as the computing resources provided by the  US Department of Energy, National Nuclear Security Administration  under Award Number  DE-NA0003968  within the  PSAAP III (INSIEME) Program  at  Stanford University.