dataesr/scientific-paragraphs-categorization huggingface dataset:
Ion-Scattering Cross-Sections Ion-scattering cross-sections with neutral species is another type of data required for the modeling of ion transport in weakly ionized plasmas. However, for ions, in contrast to the situation for electrons, there is usually no need for inelastic cross-section data but there is a need for differential elastic scattering or for some approximation thereof. For rare gas ions in their parent gas, Phelps proposed to approximate the total differential cross-section for elastic scattering as the sum of an isotropic component and a backscatter component  [157]. Figure  5  shows as an example the ion-scattering of Ar + and He + in their parent gases taken from the Phelps database. The Phelps database also contains data for Xe + in its parent gas and in Ne. In July 2017, the second database providing this type of data was introduced, namely the Viehland database [158].
Interaction Potentials Viehland has calculated interaction potentials between ions and neutral species and made them available on the LXCat website. Interaction potentials allow the evaluation the collision integral for the scattering of ions by neutral species. This allows one to calculate the ion mobility and diffusion coefficient under an electric field in a background gas  [28, 29]. In the Viehland database, there are currently interaction potential data for 91 ionic species representing a large portion of the periodic table (see also Figure  6 ) with a variety of the noble gases and H 2 resulting in 660 potentials. Figure  7  shows an example the interaction potential of Hg + 2 S 1/2 with the noble gases from the Viehland's database  [158, 160]. One can see that the interaction potential becomes repulsive at a longer internuclear distance for atoms with a higher atomic number because of their larger radius.
Swarm/Transport Data for Ions There are three databases for swarm parameters of ions: Phelps  [112] , UNAM [150] and  Viehland [158]. In these databases can be found transport parameters of ions, either derived from experiments or theory. In Figure  8  a few of the various swarm parameters that can be found on LXCat for ions are illustrated. The ions diffusion coefficients, drift velocities and mobilities in their parent gas as well as in mixtures (e. g. , air) have been tabulated as a function of other parameters (typically E/N and the gas temperature). The Phelps database has data for the ions He + , Ne + , Ar + , N + , and N + 2 in their respective parent gases  [112]. The UNAM database contains mobility parameters for CF + 3 in CF 4 , CHF + 2 in CHF 3 , and C + in Ar  [161]. The Viehland database is transcribed in part from the Gaseous Ion Transport and Rate Coefficient Database developed by Viehland  [159].
In this database are several additional parameters derived from theory following high-order moments expansion of the Boltzmann equation. Data for 424 positively or negatively charged atomic and molecular ions is available for a wide variety of elements across the periodic table of elements (see also Figure  6 ). Some of the notable changes and extensions since 2016 in the Viehland database involve ions of C  [162, 163] , Co, Cr, and Ni [164], Gd  [165] , K  [166, 167] , Mg  [168] [169] [170] [171] , O  [172, 173] , S [174], and Si  [175].
An improved description of Coulomb collisions was developed by Hagelaar and is included in the more recent versions of BOLSIG+  [180]. • ZDPlasKin: Zero-Dimensional Plasma Kinetics solver ZDPlasKin is a Fortran 90 module designed to follow the time evolution of the species densities and gas temperature in a non-thermal plasma with an arbitrarily complex chemistry  [21]. BOLSIG+ is integrated in this package. • EEDF is a user-friendly program for the numerical solution of Boltzmann equation for the Electron Energy Distribution Function in low-ionized plasma in an electric field. It is used for calculations of electron transport and kinetic coefficients in gas mixtures. EEDF comes with Data Bank, several files containing data on cross-sections for the electron-scattering from atoms and molecules  [118]  compatible with EEDF program.
These cross-section data can be found in the TRINITI database on LXCat. • BOLOS: This package provides a pure Python library for the solution of the Boltzmann equation for electrons in a non-thermal plasma. It is a multi-platform, opensource implementation compatible with the LXCat cross-section input format  [181]. • PumpKin: (pathway reduction method for plasma kinetic models) is a tool for postprocessing of results from zero-dimensional plasma kinetics solvers. The goal is to analyze the production and/or destruction mechanisms of selected species of interest, as well as to reduce complex plasma chemistry models. Only once the user is required to solve first the full chemical reaction system. The output is then used as an input for PumpKin. The PumpKin package analyzes the full chemical reaction system, and automatically determines all significant pathways in the system, i.
The code is based on the two-temperature displaced-distribution theory  [191]. Additionally, for accepting additional data from more contributors, a new staging area was added for hosting databases under a "free format". This concerns for instance different output formats of databases or databases for which the number of target species is so large that it cannot be currently be handled in a satisfactory fashion by the LXCat web interface. The latter is not considered to be a permanent solution but only to allow quicker distribution of the data. For a more detailed discussion of these aspects, we refer to Section 6. In the present staging area is made available a new XML format by Michele Renda (IFIN-HH, Particles Physics Department, Magurele, Romania) for the data available on LXCat. These data are regularly updated to consider changes made by the contributors.
Video Tutorial A video tutorial has been prepared to complement this manuscript. This video tutorial begins with an introduction to the LXCat website and proceeds to the online Data Center, where the LXCat hosted data may be accessed by users. The different types of available data are reviewed. As an example, the tutorial demonstrates how to retrieve, view, and download electron-neutral cross-sections for argon from the Phelps database  [112, 193]. The video tutorial also demonstrates how to use the online BOLSIG+ tool and the previously retrieved Phelps database cross-sections for argon to perform an all-online calculation of swarm coefficients. The results of the online calculation are then saved for later comparison and viewing. At this point, the tutorial returns to the Data Center, this time to retrieve both experimentally measured swarm coefficients, as well as previously saved results of the online calculation.
Comparison of Data On the LXCat website, it is possible to directly select different cross-sections or swarm coefficients and plot them without the need for exporting any data and use of offline programs. Such example is shown in Figure  9  with all the electron attachment crosssections on CO 2 currently present on LXCat. One can see an overall good agreement between the different databases. 6 ) Phelps  [112] , (7) SIGLO  [116]  and (8) TRINITI  [117]  databases.
LXCat Online Boltzmann Solver and Swarm Parameters Comparison The online Boltzmann solver corresponds to the March 2016 version of the BOLSIG+ freeware with default options, i. e. , the temporal growth model is assumed, and Coulomb collisions are not taken into account. Different output formats, which are not available online, are also provided in the standalone freeware version of BOLSIG+. The longitudinal diffusion coefficient is not calculated in the online version and other quantities, such as energy transport coefficients, are only available in the recent freeware versions  [179]. An important tool on the LXCat website is the possibility of generating online a BOLSIG+ database from the online Boltzmann solver, which is a temporary database created, when requested, by the user following execution of the online Boltzmann solver.
The contents of this database include swarm/transport parameters versus E/N calculated after selecting a complete dataset for each species considered in the calculation. (see Figure  10  for an example of selected datasets and some computed quantities). The data existing in this temporary database can be plotted along with measured quantities available on the other databases or compared with results from other online calculations in different gas mixtures. This temporary database is deleted when the user exits the LXCat site. A video tutorial was made to show how to perform such calculations online and how to compare the results of the calculations with data available on the website  [197]. In Figure  11  are shown swarm data for a pure CO 2 gas calculated using the Biagi database  [80, 198]    Swarm parameters calculated using the online Boltzmann solver for a pure CO 2 gas using the Biagi database  [80, 198]  and comparison with experimental swarm measurements  [133, 135,  from  Dutton [132] , ETHZ [134], Heidelberg [154], LAPLACE  [149]  and UNAM [150] databases as a function of reduced electric field.
The error associated with the kinetic model used in the tuning procedure directly contributed to the error of the cross-section set. That is, a cross-section set derived using a two-term Boltzmann equation model features all the assumptions and limitations associated with the two-term approximation. Moreover, it has been demonstrated that the ability to generate a set of swarm coefficients is not unique to a single set of cross-sections  [7]. The quality of a given data set can only be evaluated within the theoretical framework for which it was derived. Its reuse and evaluation using for instance a multi-term Boltzmann equation model will thus lead to differences that are not only related to intrinsic limitations of the used physical model. Application of a cross-sections dataset using the two-term approximation in a multi-term Boltzmann equation model, or Monte Carlo/PIC model is not recommended and will likely yield non-negligible error.
Mixing cross-sections data sets or using incomplete sets Most cross-section sets hosted by LXCat were produced via the aforementioned procedure of matching calculated and measured swarm coefficients. These complete cross-section sets are considered to be self-consistent, where the various pathways for electron power loss, deflection, and so on, cumulatively contribute to achieving the desired power balance and correct swarm coefficients. Introducing or substituting cross sections from other sources will affect this power balance and violate the self-consistency of the set. Similarly, the omission of cross-sections from a complete set will also violate the self-consistency of the set. Users are recommended to use the complete set of cross-sections when applying these data in their models and are urged to not mix data from various sources.
e. , experimental data from an SST apparatus should only be compared with a model configured to represent SST conditions. Similarly, experimental data from a PT configuration should only be compared with a model configured to represent PT conditions. Users are again recommended to review the relevant sources and publications associated with the experimental swarm data, as well as the notes and comments included with the LXCat file containing the data to determine the conditions that these data were collected. Many of the publicly available tools for performing kinetic calculations feature the ability to select the growth model, although not all codes use the same terminology. The standalone version of BOLSIG+ allows for the selection of either a PT or SST growth model, while the online BOLSIG+ tool uses a PT configuration.
• Treatment of three-body collisions Some cross-section sets include three-body cross-sections, where a single electron collides with a pair of neutral targets, which results in a pressure dependence of the crosssection. These three-body cross-sections are often normalized to the neutral species density, such that they are easily incorporated into an existing model via simply multiplying this cross-section by the background gas density. The user should pay attention to the background density at which the apparent 2-body cross-section was derived that can differ for different databases.
• The data exchange format, the data model and the choice for a database type; • The overall framework design. 6. 1. The Exchange Format and Choice for a Database Type The data exchange format was originally designed for one particular purpose: the exchange of complete cross-sections sets for a discharge that is governed by elastic electronscattering, electron-impact excitation and ionization and perhaps electron attachment. Such data are tuned to give excellent results for transport coefficients and rate coefficients when used in combination with a Boltzmann solver (see Section 2 for more detail). Interestingly, such calculations can be done without any knowledge of the target particle's precise electronic or, for molecules, its rovibrational configuration. This is demonstrated by the appearance of compound states such as Ar * in LXCat.
In the case of an excitation process the input file merely needs to provide the names of the initial and final states of the atom or molecule, the threshold energy of the process and the cross-section data. This can be seen in Figure  12  which shows an excerpt from the Phelps database  [112]. ----------------------------1. 150000 e +1 0. 000000 e +0 1. 270000 e +1 7. 000000 e -22 < omitted lines > -  ---------------------------  Although highly flexible, the current LXCat file format poses a few challenges in practice. First, a custom parser is often required, and the lack of a formal schema makes it difficult to verify the integrity of the document. Second, some fields are used in a redundant manner (c. f. lines 2-6) which can lead to confusion in parsing and on what is relevant to a given model.
Third, there are several relevant quantities for new data sets which cannot be expressed in a consistent manner. As an example, if the database entry refers to a particular state of argon such as Ar( 1 S 0 ), there is no method to detect that the state has been defined using the LS coupling scheme. Furthermore, the use of different notation schemes by different authors makes it difficult to reliably infer the parameters S = 0 and L = 0. This problem is often circumvented by the inclusion of such information in the form of contributor-specific annotations in the comment blocks. As an example, the Lisbon database for N 2  [101]  contains comments specifying detailed state information that is used by the LoKI-B Boltzmann solver  [187]. This observation suggests the possibility of improving on the original format by the inclusion of optional lines such as "S: 0".
Unfortunately, this straightforward approach poses new complications for the backend. Presently, LXCat uses an SQL database to store its data with every row corresponding to a data item. If excited states were to be added in the way described above, both the name and the LS parameters would need to be encoded as new columns in the current schema. Conceptually, the layout would be similar to that found in Table  1. This table illustrates one explicit and one implicit problem with the aforementioned approach. The explicit problem is the proliferation of NULL values in the table. These are necessary for species where a particular coupling scheme is not applicable. In this case, neither e nor Ar * are described by the LS coupling scheme. The larger, implicit problem is that the addition of each new optional parameter affects the entire table, even those entries for which the parameter is not relevant.
These issues suggest the need to reconsider the LXCat backend to better serve the community. Although some techniques exist to ameliorate these issues (e. g. , table indirection), they do not solve the fundamental problem which is that table-based databases are not well suited for heterogeneous data sets. In recent months we have created an experimental implementation of LXCat that takes advantage of modern concepts in computer science, such as the JSON file format and graph or hybrid databases. Although considerably simplified, it provides an idea of the possibilities that are offered by reconsidering LXCat's data structures. Let us first look at Figure  13 , which shows the JSON equivalent of the content of the SQL table in Table  1. [ { " particle " : " e " , " charge " : -1 } , { " particle " : " Ar " , " charge " : 0 , " e " : " * " } , { " particle " : " Ar " , " charge " : 0 , " S " : 0 , " L " : 0 , " Parity " : " Even " , " J " : 0 } ] Figure  13.
We have experimented with both graph and hybrid databases, in which JSON objects are treated as first-class citizens. Where traditional, relational databases store rows of data in tables, these databases store collections of JSON objects, quite like Figure  13. Furthermore, a graph database, as the name suggests, allows objects to be addressed in terms of their relations to each other. This type of data structure is expected to be very beneficial with the type of data on LXCat where hierarchical relations exist between states, and there are networks of reactions with arbitrary types. Switching to a flexible, yet structured framework, with a graph or a multi-model database at its core promises to enhance LXCat's current capabilities while simultaneously opening the door for a future chemistry database.
Framework Implementation Conceptually, the present implementation of LXCat consists of two halves: the SQL database and the website. The latter provides the interface that allows users request data. This request is then translated into a database query, the results of which are served to the user in the form of a graph that is displayed on a screen or a file that can be downloaded. At present, the two halves are tightly coupled and there is no abstraction defining how the database can be accessed. This situation is depicted in Figure  14a. This approach has various disadvantages. First, from the project management point of view the direct access of the database violates the principle of separation of concerns. This violation poses practical challenges. As an example, a graphic designer updating the appearance of LXCat must be careful not to accidentally alter database queries that appear in the same files.
Moreover, this approach hampers code reuse both internally and externally. One can envision plasma modeling tools such as BOLSIG+  [27] , LoKI-B  [187] , HPEM  [224]  and PLASIMO  [225] , providing integrated access to data sets on LXCat with a suitable abstraction. Such implementation would of course have to abide to the LXCat policy on data redistribution with the written consent required on a case-by-case basis between the contributors and the third parties (see Appendix B). This situation can be improved by inserting an Application Programming Interface (API) layer between the database and the website or other front-end. This layer is comprised of a set of endpoints that provide well-defined stable interfaces to the database backend. The endpoints take care of the communication with the database making the website agnostic to the type of backend.
The LXCat project largely provides cross-sections for reactions which are required for modeling electron and ion-swarm parameters in non-equilibrium low-temperature plasmas. However, there are additional reactions which are needed for a full description of the electron and ion kinetics such as electron-ion recombination, dissociative recombination or attachment, three-body and charge exchange processes. Due to the internal complexities of the database organization, such an extension still requires a significant effort. Work is ongoing for supporting for these additional reaction types and new data formats that can help addressing such issues was outlined in Section 6. 1. In Section 6, we discussed possibilities for a new framework implementation of LXCat that would allow addressing more functionalities on the website and for interactions with the databases.
One benefit would be for instance allowing proper use and storage of coupling schemes used for defining excited levels in atoms and molecules. Different communities of users of cross-sections have adopted different notations (e. g. , L-S coupling, Racah notation, Paschen notation,. ) due to historical reasons. These notations can be translated into one another if the notation used in the database is flagged and that sufficient information on the states is stored such that an unambiguous conversion between notations can be made. The proposed implementation would also allow considering on an equal footing the species on the left and on the right-hand side of the collisional process. This is important for considering state-to-state processes, particularly in the case when forward and backward (i.
Conclusions LTP modeling is a significant challenge that requires a great deal of atomic and molecular data. This applies regardless of whether it is a global, kinetic, or fluid model. LXCat was born out of this need for data, initially supplying electron-scattering databases that were carefully calibrated to swarm experiments but applicable more broadly. As a digital platform, it obviated the need for "traditional" data extraction, allowed wider access to essential data, and enabled reproducible plasma simulations. Since its inception, LXCat has grown substantially. This began with the inclusion of electron-scattering data derived from quantum mechanical models, soon followed by the inclusion of ion-neutral interaction potentials, differential scattering cross-sections, oscillator strengths, and swarm data.
It has also become a more general plasma modeling resource with the incorporation of a web interface for BOLSIG+, links to numerous compatible software packages, and through its ongoing publication of comparative analyses for different gases of complete data sets. Not only has the content of LXCat grown, but its participants-contributors, users, and maintainers alike-now touch nearly every part of the globe, forming a truly international collaboration. Looking forward, there are many plans in motion to improve LXCat for its users and contributors. Database enhancements are underway to make new data types available for use. In parallel, there is an ongoing internal research effort on improved data formats and database technologies. Improvements in this area will provide users with powerful new sorting and comparison mechanisms, increase the ways in which contributors can identify and categorize their data, and improve the resilience of the project as a whole.
Finally, there are nascent efforts to address the growing need of the community for non-equilibrium plasma chemistry data in the form of reaction rate databases  [36]. In summary, there are several efforts in progress to extend and continue LXCat's broad impact. However, this work cannot continue without the ongoing support of LXCat's users and contributors. Of the users, we ask that you always cite the data that you use, we seek your feedback on what could be improved, and hope that you consider joining the project in a more active role. Of our contributors, we gratefully acknowledge your ongoing support and likewise ask that you continue to tell us how to make the data sharing process easier for you and welcome your suggestions on future developments. Ultimately, LXCat is a grassroots organization whose health depends on the same community that it supports.