dataesr/scientific-paragraphs-categorization huggingface dataset:
Plackett-Burman screening study XLstat, an add-on for the Microsoft Excel ® software, was used to generate the Plackett-Burman design used for studying the effects of the synthesis parameters on the properties and activity of Zn-Ta-TUD-1 and analyze the responses obtained experimentally (Table  1 ). XLstat can model the effect of each parameter (also known as variable or factor) of a given response by fitting a first-order polynomial function of the studied parameters (equation 5) with the experimental response. = + • + ( 5 ) where Yj is the fitted response, β0 the model intercept, βi is the linear coefficient of independent variable i with Xi its level, k the number of involved variables, and ε the residual error. Equation  5 was solved using the least square method, which is a multiple regression technique that fits mathematical models to experimental data by minimizing the value of residuals between experimental and fitted responses.
The order by which the chelating agent was added to the precursor solution (ChOrd) with regards to the metal precursor was also investigated out of curiosity. Fig. 2  illustrates the Zn-Ta-TUD-1 synthesis methods used in the PB experiment, as well as the different levels of all parameters with the exception Zn:Ta and Alk:Si. Choosing the two levels of each factor, represented by + and -in Table  1 , was largely a matter of preliminary experimentation with the TUD-1 and the result of our unpublished screening study previously mentioned. Table  2  lists the levels of each variable investigated in the Zn-Ta-TUD-1 synthesis; Fig. 2  illustrates these levels in relation to the Zn-Ta-TUD-1 preparation procedure. Experiments were performed in a random order generated by the XLStat software to minimize errors and biases.
Response surface methodology RSM is a technique that encompasses multi-variant experimental design, statistical modelling and process optimization. It is generally performed in three steps: (1) DOE, (2) response surface modelling through regression and (3) optimization of the response  [44]. The XLstat software was used for all three steps. RSM was used to optimize the productivity in BD (YPDB) by establishing its relationship to two independent variables: Zn and Ta molar content in Zn-Ta-TUD-1, Zn mol. % and Ta mol. % respectively. The variables were selected after the PB screening study showed that the Zn:Ta molar ratio had a significant effect on the activity of the catalyst. In addition, the Zn-Ta-TUD-1 preparation method used corresponded to the best performing procedure identified by screening, which was equivalent to that used for sample PB12 in Table  1.
For a single-response, two-variable experiment, a three-level full factorial design was found suitable, as it did not require many experiments, yet provided a reasonable amount of information  [35]. The three levels used were symbolized by -1, 0, 1. Table  3  lists the experimental design, the corresponding experimental values for each level and the YPBD response obtained via catalytic testing. Like above, experiments were performed in random order to minimize errors and biases via the XLstat software. Response surface modelling was performed by an empirical quadratic model of the response (Equation  6 ) to the experimental data using the least square root method. = + • ! + • ! " + • ! # • ! + ( 6 ) where Yj is the fitted response, β0 the model intercept, βi is the linear coefficient of independent variable i with xi its input factor, and k the number of involved variables, βi is the quadratic coefficient of variable i, βij is the linear interaction coefficient between variable i and j, and ε the residual error.
For species introduced by reactions added or updated in this work, their thermochemical data originate from the same publications  [6 , 34]  as corresponding reactions. For some reactions, theoretically computed rate constants from both forward and reverse directions are available, so they are expressed in a pair of irreversible reactions with separate rate constants in the model. This practice can help to eliminate the errors in reaction rates brought by the uncertainties and potential inconsistency in the thermochemical data. All simulations in the current work were performed with the homogenous reactor model of the software COSILAB  [44]. The nominal reaction time of 4. 0 ms and the constant pressure of 20 bar were used in the simulations. The constant pressure assumption typically used in simulating the speciation results sampled from single-pulse shock tube experiments has been well justified in previous publications  [45 , 46].
This is characteristic of uranium(IV) which is a magnetic singlet at low temperature but that exhibits a small contribution from temperature independent paramagnetism to give a nonzero magnetic moment. The  11   9 )  65. Indeed, trace resonances that match reported data 65 for 9 could be observed. A variable-temperature 1 H and 11 B{ 1 H} NMR study (Supplementary Figs. 12, 13 ) reveals that at 293 K the dominant products are 4 and free BPh 3 , but as the temperature is lowered to 253 and then 233 K resonances attributable to 8 grow in as 4 diminishes such that at 253 K the ratio of 4:8 is ~2:1 and at 233 K this ratio is ~2:3. However, when 9 is treated with H 3 NBPh 3 the formation of 4 and BPh 3 are observed by 1 H NMR spectroscopy. This suggests facile, unspecific reversible reactivity but also hints at FLP-type reactivity, so we dissolved a 1:1 mixture of 4 and BPh 3 under H 2 (1 atm.
Yield of 8: 0. 16 g, 62%. Anal. calcd for C 51 H 92 BN 5 Si 3 U: C, 55. 26; H, 8. 37; N, 6. 32%. Found: C, 55. 52; H, 8. 16; N, 5. 91%. NMR spectroscopy reveals that when isolated 8 is dissolved in solution it dissociates to 4 and free BPh 3 and also trace H 3 NBPh 3 and 9, but this equilibrium can be manipulated by cooling samples favouring the formation of 8 so a variable-temperature NMR study was performed, see below. The presence of H 3 NBPh 3 could not be unequivocally confirmed in the 1 H NMR spectrum due to its low concentration level in a spectrum dominated by paragmagnetic species, but its presence is confirmed by  11  B NMR spectroscopy. Trace resonances corresponding to reported data for 9 could be observed  65. 11  Variable-Temperature NMR study of 8. A brown solution of 4 (0. 04 g, 0.
Acknowledgements We gratefully acknowledge funding and support from the  UK Engineering and Physical Sciences Research Council  (grants  EP/K024000/1 ,  EP/M027015/1 , and  EP/P001386/1 ),  European Research Council  (grant  CoG612724 ),  Royal Society  (grant  UF110005 ),  Humboldt Foundation ,  CalMip ,  The National EPSRC UK EPR Facility, The University of Manchester ,  COST Action   CM1006 , and the  Leverhulme Trust UK  for a research fellowship to FT. We thank  Prof. D. W. Stephan  ( University of Toronto ) for insightful discussions about this work.
The experimental curves were fitted, after subtraction of the Shirley-type background, with a combination of Gaussian and Lorentzian lines of a constant proportion (70:30) with the use of CasaXPS 2. 3. 19 software. The Co 2p and Ni 2p lines were deconvoluted with a relative intensity ratio of 2p 3/2 and 2p 1/2 components fixed to 2:1. The BE values were charge-corrected to the carbon C 1s excitation which was set at 285. 0 eV.
Particle phase analysis Particle phase data are collected every 10 min in the aerodynamic diameter range 9. 82 -414. 20 nm using a Scanning Mobility Particle Sizer (SMPS) supplied by TSI. The SMPS consists in a Condensation Particle Counter (CPC) TSI 3800 coupled with a Diffusion Mobility Analyzer (DMA). The SMPS is located in the center of the room which allows the sampling of aerosols directly from the air inside the room at a continuous flow rate of 600 mL min -1.
This level is in accordance with formerly reported data related to the validation IRINA  [24]. Second, background levels of particles are monitored for one hour in the presence of both devices to assess the impact of their respective air flows on the background particle level in IRINA. Results of the background number of particles both in the presence and in the absence of air purifiers are presented in Table  2. As reported in this figure, the variation of the number of particles in IRINA remains within the measurement uncertainties in the absence of any VOC, thereby device operations do no lead to any significant resuspension and do not noticeably impact the background levels of particles. The evolution of the number of particles as a function of time during the treatment of VOCs emitted by household product using both devices, at startup, is shown in Figure  10  along with mean background level of particles (grey dashed line) and background variation zone (dashed rectangle) in IRINA.
A. Fixed window scans To get an overview of the various dynamic processes setting in at different temperatures in the systems under investigation, elastic (EFWS) and inelastic fixed window scans (IFWS) are conducted in a temperature range from 2 K to 355 K. While heating the specimens with a rate of 1 K/min, alternately the intensity of the elastically scattered neutrons, i. e. ∆E = 0 µeV and those having experienced an energy change of ∆E = ±2 µeV is measured. Figure  3  shows the acquired data from such an IFWS at the example of the bulk [BuPy][Tf 2 N] (left panel), which is measured as a reference for the subsequent analysis of the respective cation dynamics in nanoconfinement (right panel). This comparison already impressively illustrates the confinement-induced alterations in the phase transition behaviour, as well as the Q-dependence of the data at different temperatures, giving first hints on the nature of the molecular dynamics.
(3) I 0 is an intensity factor and c 0 a constant offset. Both are containing a contribution originating in the convolution of the dynamic structure factor (Eq. 1) with the resolution function of the instrument. [43]  The exponential prefactor describes the temperature-dependence of the Debye-Waller factor  [60] , determined by a respective fit to the data in the low-temperature region of the corresponding EFWS (cp. Fig. 4 a ), before any molecular dynamics aside from lattice vibrations sets in. The constant offset c 0 is ascertained in the same temperature region, but from the IFWS. As can be seen from Fig. 5 , the employed model fits the measured data very well. It yields an activation energy of 9. 7 kJ/mol for these localised motions. This value is larger than those obtained by Burankova et al.
[68]  Alike for supercooled water in silica nanopores such a pore-size dependence of the activation energy is observed. [69]  Similarly in the case of the data acquired on IN16B with its higher resolution but smaller dynamic range compared to FOCUS, two dynamic components are found. One of these is ascribed to the superposition of the slow localised dynamics, as found from the IFWS, and the diffusive motion, as seen with FOCUS. However, since they possess both a comparable HWHM, a separation of both components is challenging and the analysis is focussed to the second, much narrower component, here. The latter is of diffusive nature and its HWHM exhibits again a behaviour, following the Singwi-Sjölander jumpdiffusion model. The corresponding self-diffusion coefficients obtained from these IN16B spectra are almost one order of magnitude smaller (see filled circles in Fig.
ACKNOWLEDGMENTS We are indebted to  Alexei Kornyshev  ( Imperial College, London ) and  Yury Gogotsi  ( Drexel University, Philadelphia ) for useful discussions. Furthermore, we thank the working group of  Rolf Hempelmann  ( Saarland University ) for providing the ionic liquid. M. B. and P. H. acknowledge support by the  Deutsche Forschungsgemeinschaft  within the project " Property Changes of Multiphasic Fluids by Geometrical Confinement in Advanced Mesoporous Materials " (Project No. 407319385 ) and the  DFG Graduate School   GRK 2462  " Processes in natural and technical Particle-Fluid-Systems (PintPFS) " (Project No. 390794421 ).
Effects of concentration, temperature and anion The selectivity of propylene over propane and the mixed gas permeability for different silver salt composite membranes are shown in Figure  6  with the data provided in Table  S2  of the supporting information. The results for the 20 wt. % and 30 wt. % AgNO3 membranes are not shown as no further improvement in the separation was achieved at these higher loadings of salt. Moreover, after these membranes had been repeatedly synthesized and tested 5 times, microscopy images indicated that these membranes were porous in structure instead of being dense membranes, negating any meaningful comparison of the transport properties. The selectivity and gas permeability measured for the pure TPU polymeric membrane are 2. 0 and 1900. 2 Barrers, respectively at 293 K.
Working electrodes (WEs) were cleaned by rinsing them with ethanol for 5 minutes, and then they were properly rinsed with deionized water. They were then dried under steam of nitrogen. The surface WEs were then cleaned from organic contaminants by using UV/O3 (UV/Ozone ProCleanerTM, BioForce Nanosciences) for 30 min. The device was connected to the potentiostat VMP3. Analysis was monitored and modeled using the EC-Lab software. Electrochemical deposition of 4-aminophenylacetic acid 98% (CMA) was made by using 5 mM of CMA in water with sodium nitrite 15 mM and HCl 15 mM. Both sodium nitrite and HCl solutions were added to the solution of CMA and kept in an ice bath for 15 minutes. This electrode preparation approach was adapted from that reported by  Allongue et al. (1997)  [27]. The final solution was kept at 0 °C and immediately used.
The reductive absorption of the salt onto the electrode was achieved by four repetitive scans of CV between 0. 3 and -1. 0 V at 200 mV s -1. Figure  2  shows a schematic illustration of CMA deposition onto gold WEs. Working electrodes (WEs) were cleaned by rinsing them with ethanol for 5 minutes, and then they were properly rinsed with deionized water. They were then dried under steam of nitrogen. The surface WEs were then cleaned from organic contaminants by using UV/O 3 (UV/Ozone ProCleanerTM, BioForce Nanosciences) for 30 min. The device was connected to the potentiostat VMP3. Analysis was monitored and modeled using the EC-Lab software. Electrochemical deposition of 4-aminophenylacetic acid 98% (CMA) was made by using 5 mM of CMA in water with sodium nitrite 15 mM and HCl 15 mM. Both sodium nitrite and HCl solutions were added to the solution of CMA and kept in an ice bath for 15 min.
Funding: The authors acknowledge the financial support from the projects European Communities Seventh Framework Program: SEA-on-a-CHIP ( FP7-OCEAN-2013)  under the grant agreement N • 614168, and funding from the  European Union 's  Horizon 2020 research and innovation program  entitled  KardiaTool  under grant agreement N •  643694 , and the fellowship from  Science Without Borders program-Conselho Nacional de Desenvolvimento Ciêntífico Tenológico (CNPq)-Brazil  grant  N • 249056/2013-5.
The system allows suppression of the possible fluorescence interference. The data were collected with the Raman shift range from 100 to 1100 cm -1 with the spectral resolution of 10 cm -1. Energy dispersive X-ray spectroscopy (SEM-EDS, Zeiss Ultra Plus, Germany,) was used to observe the amount of sulfur on the used sample. Prior to the measurements, the sample was coated with carbon. X-ray photoelectron spectroscopy (XPS) analysis was performed with a Thermo Fisher Scientific ESCALab 250Xi spectrometer (Waltham, MA, USA) with a monochromatic Al K α (1486. 6 eV) radiation source operated pass energy of 20 eV. Data analysis was performed by the ThermoAvantage TM software (v5. 957, Thermo Fisher Scientific Inc. , Waltham, MA, USA) and mixed Gaussian-Lorentzian function was used in the fitting of signal.
XAS XAS data were collected for all the samples and also some Mn references at BM23 beamline  [28]  of the European Synchrotron Radiation Facility (ESRF), Grenoble (ring energy was 6. 0 GeV and the current 150-200 mA). Two Si (111) crystals were used as a monochromator and a pair of Si-coated mirrors with a glancing angle of 3 mrad was employed to reject high-energy harmonics. Energy was calibrated by using a Mn foil reference. Spectra in transmission were recorded with ionization chambers filled at 2 bar with a N 2 /He mixture with the appropriate ratios to obtain an absorption of 0. 3 in the I0 and 0. 7 in I1. Spectra in fluorescence mode were recorded with a silicon Vortex detector placed at 90°with respect to the incident X-ray beam. EXAFS spectra of the calcined samples were taken integrating 2 s per point until the edge and with a linearly increasing integration time until 10 s per point above the edge.
9999. The XANES spectra of those components correspond to MnO 2 , Mn 2 O 3 , Mn 3 O 4 and MnO, respectively. Thus, these four spectra were used in a linear combination fitting of the XANES spectra recorded during TPR. Artemis program, also part of Demeter package 0. 9. 21  [29] , was used for EXAFS analysis. The fitting of χ(k) was simultaneously performed in three k-weights (χ(k)•k, χ(k)•k 2 and χ(k)•k 3 ), in order to correctly represent both the light and the heavy atoms. Paths phases and amplitudes were calculated, for all models, with the Feff6 program contained in Artemis. To perform the Fourier transform of the k space a Hanning window from 2. 9 to 8. 1 Å -1 (dk = 1. 5 Å -1 ) was chosen for all spectra. Appropriate window limits in the R space, where the fit took place, were chosen for each spectrum.
Louis, MO, USA). The air purifier was placed in the test chamber equipped with a temperature and hygrometry probe (Testo 171, Forbach, France) and a fan (flow rate of 190 m 3 h -1 ). Humid clean air Zero (about 50% relative humidity) was supplied to the chamber by an air zero generator (F-DGS, Evry, France). Temperature was maintained at about 25°C. A mixture of the 5 VOC was injected in the chamber via a septum and, after concentration stabilization in the air chamber, the purifier was turned ON. [34]  VOC, CO2, ozone and water in the chamber were continuously monitored by SIFT-MS throughout the test using positive and negative ionization modes simultaneously. These data were compared to the results of conventional analysis methods. In parallel with the SIFT-MS measurements, acetone, heptane and toluene on the one hand, and carbon dioxide on the other hand, were automatically monitored by on-line gas chromatography (GC-FID for VOC and GCmethanizer-FID for CO2 , Chromatotech, Saint Antoine, France) connected to the test chamber.
All calculations were performed by means of the Spartan software  [48]. Possible geometries were generated at the molecular mechanics level. All structures were afterwards optimized by means of DFT calculations. For the single ions EMI and TfO, the B3LYP functional was employed considering the ions as isolated in vacuum; this particular functional is considered as a benchmark for this type of calculation  [12]. For the ionic couple EMI-TfO, the ωB97X-D functional, considering both the empirical dispersion corrections and the presence of a polar solvent (dimethylformamide, εr = 37. 22), was used. Indeed, this last combination of functional, dispersion forces and polar solvent has recently provided a good description of the absorbance spectra of diethyl methyl ammonium methanesulfonate (DEMA-MS) and diethyl methyl ammonium trifluoromethanesulfonate (DEMA-TfO)  [49].
NaCl was used as a pressure-transmitting medium and to reduce the sample thickness and avoid signal saturation  [46]. Pressure was measured in-situ through the standard ruby luminescence technique  [47]. The luminescence was excited and collected using a home-built optical setup aligned with the Schwarzschild objectives and made of dichroic mirrors, a 532 nm green laser, a camera, a lamp and a fiber collimator connected to an Ocean Optics HR4000 spectrometer. Before acquiring each spectrum, we waited for about five minutes to achieve pressure stabilization. All calculations were performed by means of the Spartan software  [48]. Possible geometries were generated at the molecular mechanics level. All structures were afterwards optimized by means of DFT calculations. For the single ions EMI and TfO, the B3LYP functional was employed considering the ions as isolated in vacuum; this particular functional is considered as a benchmark for this type of calculation  [12].
Method to estimate the molecular diffusivity of VOC i in air Calculation of the convective mass transfer coefficient, hi, for VOC i depends on the experimental conditions and on the molecular diffusivity coefficient of VOC i. This value must therefore be individually determined for each VOC. However, molecular diffusivity coefficient values were found for five VOCs in the GSI chemical database, except for pentanal, hexanal, and terpenes. Among the chemical property estimation methods present in the literature, the method proposed by  Fuller et al. (1969)  can be used to estimate the molecular diffusivity coefficient of a binary gas-phase system based on the molar weight and the atomic diffusion volume  (Fuller et al. , 1969 (Fuller et al. , , 1966;; Fuller and Giddings, 1965). Based on an empirical relationship proposed by  Fuller et al.
The sensitivity of VOC emissions to temperature underscores the need to consider this parameter when setting up experimental tests, especially under unstable temperature conditions. From the relative concentration enhancement parameter (Equation  2 ), the concentration datasets can be corrected for temperature when the temperature fluctuates during experiments. However, it is not always necessary to correct data with respect to temperature, and VOC concentrations should only be corrected when large temperature variations occur, particularly in long-term experiments. According to the literature, the effect of RH on VOC emissions does not show any particular trends. Indeed, authors report a variable influence of RH on VOC emissions depending on the VOC-material system considered  (Colombo et al.
Specific influence of air velocity over the material surface on VOC emission rates The impact of changes in the air velocity near to the material's surface on VOC emissions from PB was studied by determining the emission rates for VOCs when applying different air velocities over the material's surface at a constant ACR. The corresponding data are reported in Figure  7. Since a single material sample was used for this series of tests, datasets were corrected to account for VOC depletion, assuming a constant depletion rate over the series of tests. Among the VOCs monitored, acetone, hexanal and formaldehyde presented the highest emission rates, with values exceeding 280 µg. m -2. h -  ; the emission rates for other VOCs were less than 75 µg. m -2. h -. According to our data (Figure  7 ), the air velocity over the PB surface did not significantly affect emission rates for the eight VOCs monitored.
Material scale investigation In contrast to the previous series of tests, each experimental protocol alternately analysing airtight/ventilated emission lasted for a full week. Over the course of these experiments, temperature varied in line with day-night cycles, with fluctuations from 20 to 25 °C. Maximum temperatures were measured during the day due to sunlight. To account for these variations, a data correction was applied to concentration profiles using Equation  8 , considering an identical influence of temperature on VOC emission in both steady state and transient conditions. In Equation  8 , Ccorr,i is the temperature corrected concentration (ppb) of VOC i, Cexp,i is the experimental concentration (ppb) of VOC i, Tref is the reference temperature set at 21 °C, Texp is the experimental temperature and αi is the relative concentration enhancement of VOC i per degree Celsius, as described in Equation  2.