Adamant: a JSON schema-based metadata editor for research data management workflows [version 1; peer review: 2 approved]

The web tool Adamant has been developed to systematically collect research metadata as early as the conception of the experiment. Adamant enables a continuous, consistent, and transparent research data management (RDM) process, which is a key element of good scientific practice ensuring the path to Findable, Accessible, Interoperable, Reusable (FAIR) research data. It simplifies the creation of on-demand metadata schemas and the collection of metadata according to established or new standards. The approach is based on JavaScript Object Notation (JSON) schema, where any valid schema can be presented as an interactive web-form. Furthermore, Adamant eases the integration of numerous available RDM methods and software tools into the everyday research activities of especially small independent laboratories. A programming interface allows programmatic integration with other software tools such as electronic lab books or repositories. The user interface (UI) of Adamant is designed to be as user friendly as possible. Each UI element is self-explanatory and intuitive to use, which makes it accessible for users that have little to no experience with JSON format and programming in general. Several examples of research data management workflows that can be implemented using Adamant are introduced. Adamant (client-only version) is available from: https://plasma-mds.github.io/adamant

Introduction and verification of FEDM, an open-source FEniCS-based discharge modelling code

This paper introduces the FEDM (Finite Element Discharge Modelling) code, which was developed using the open-source computing platform FEniCS (https://fenicsproject.org). Building on FEniCS, the FEDM code utilises the finite element method to solve partial differential equations. It extends FEniCS with features that allow the automated implementation and numerical solution of fully-coupled fluid-Poisson models including an arbitrary number of particle balance equations. The code is verified using the method of exact solutions and benchmarking. The physically based examples of a time-of-flight experiment, a positive streamer discharge in atmospheric-pressure air and a low-pressure glow discharge in argon are used as rigorous test cases for the developed modelling code and to illustrate its capabilities. The performance of the code is compared to the commercial software package COMSOL Multiphysics\textsuperscript{\textregistered} and a comparable parallel speed-up is obtained. It is shown that the iterative solver implemented by FEDM performs particularly well on high-performance compute clusters.Comment: 17 pages, 12 figures, revision submitted to Plasma Sources Science and Technolog

Towards a Machine-Learned Poisson Solver for Low-Temperature Plasma Simulations in Complex Geometries

Poisson's equation plays an important role in modeling many physical systems. In electrostatic self-consistent low-temperature plasma (LTP) simulations, Poisson's equation is solved at each simulation time step, which can amount to a significant computational cost for the entire simulation. In this paper, we describe the development of a generic machine-learned Poisson solver specifically designed for the requirements of LTP simulations in complex 2D reactor geometries on structured Cartesian grids. Here, the reactor geometries can consist of inner electrodes and dielectric materials as often found in LTP simulations. The approach leverages a hybrid CNN-transformer network architecture in combination with a weighted multiterm loss function. We train the network using highly-randomized synthetic data to ensure the generalizability of the learned solver to unseen reactor geometries. The results demonstrate that the learned solver is able to produce quantitatively and qualitatively accurate solutions. Furthermore, it generalizes well on new reactor geometries such as reference geometries found in the literature. To increase the numerical accuracy of the solutions required in LTP simulations, we employ a conventional iterative solver to refine the raw predictions, especially to recover the high-frequency features not resolved by the initial prediction. With this, the proposed learned Poisson solver provides the required accuracy and is potentially faster than a pure GPU-based conventional iterative solver. This opens up new possibilities for developing a generic and high-performing learned Poisson solver for LTP systems in complex geometries

Modeling of Atmospheric-Pressure Dielectric Barrier Discharges in Argon with Small Admixtures of Tetramethylsilane

A time-dependent, spatially one-dimensional fluid-Poisson model is applied to analyze the impact of small amounts of tetramethylsilane (TMS) as precursor on the discharge characteristics of an atmospheric-pressure dielectric barrier discharge (DBD) in argon. Based on an established reaction kinetics for argon, it includes a plasma chemistry for TMS, which is validated by measurements of the ignition voltage at the frequency f=86.2kHz for TMS amounts of up to 200 ppm. Details of both a reduced Ar-TMS reaction kinetics scheme and an extended plasma-chemistry model involving about 60 species and 580 reactions related to TMS are given. It is found that good agreement between measured and calculated data can be obtained, when assuming that 25% of the reactions of TMS with excited argon atoms with a rate coefficient of 3.0×10−16m3/s lead to the production of electrons due to Penning ionization. Modeling results for an applied voltage Ua,0=4kV show that TMS is depleted during the residence time of the plasma in the DBD, where the percentage consumption of TMS decreases with increasing TMS fraction because only a finite number of excited argon species is available to dissociate and/or ionize the precursor via energy transfer. Main species resulting from that TMS depletion are presented and discussed. In particular, the analysis clearly indicates that trimethylsilyl cations can be considered to be mainly responsible for the film formation

Plasma parameters of microarcs towards minuscule discharge gap

This paper describes the behaviour of the plasma parameters of microarcs generated between a cooled copper anode and a ceriated tungsten cathode by means of a one-dimensional unified non-equilibrium model for gap lengths between 15 and 200 μm and current densities from 2 × 105 up to 106 A/m2. The results obtained show that the decrease of the gap length to a few tens of micrometres for a given current density results in a progressive shrinking of the quasi-neutral bulk in the microplasma and its complete disappearance. The decrease of the gap length further leads to an increase of the discharge voltage and the electron temperature and to slightly less heating of the gas. © 2020 The Authors. Contributions to Plasma Physics Published by Wiley-VCH Verlag GmbH & Co. KGa

Plasma-MDS, a metadata schema for plasma science with examples from plasma technology

A metadata schema, named Plasma-MDS, is introduced to support research data management in plasma science. Plasma-MDS is suitable to facilitate the publication of research data following the FAIR principles in domain-specific repositories and with this the reuse of research data for data driven plasma science. In accordance with common features in plasma science and technology, the metadata schema bases on the concept to separately describe the source generating the plasma, the medium in which the plasma is operated in, the target the plasma is acting on, and the diagnostics used for investigation of the process under consideration. These four basic schema elements are supplemented by a schema element with various attributes for description of the resources, i.e. the digital data obtained by the applied diagnostic procedures. The metadata schema is first applied for the annotation of datasets published in INPTDAT -- the interdisciplinary data platform for plasma technology.Comment: 15 pages, 1 figure, 10 table

What does data stewardship mean in physics?

This article expands on the considerations on data stewardship in physics the authors have presented as a poster at the “Data Stewardship goes Germany” workshop held in Brunswick in October 2022. We start from the observation that despite the close links between research in physics and scientific computing as a tenet of research data management (RDM), currently, the research data produced by physicists are not as FAIR (findable, accessible, interoperable, and reusable) as they could and should be. Physics research groups in Germany as of now do not feature explicitly designated data stewards. Building on a survey on RDM in physics conducted among researchers in 2020, we lay out a clear case and a mission for more explicitly defined and acknowledged data stewardship in physics. We argue that because of the closeness between data stewardship and genuine research, ample domain knowledge is indispensable: Data stewards in physics should ideally be trained physicists themselves! Data stewards are going to face a heterogeneous research landscape in terms of group size and resources, defined by the pressure to “publish or perish”. We consider that the introduction of data stewardship presents an opportunity to the physics community to self-organize research support infrastructures where they are missing. Data stewards from the physics community would be ideally skilled to transform the existing data handling solutions into the RDM systems needed to achieve a future of FAIR data from physics. We envision them to contribute to scientific projects both as advisors and as active role models of good scientific practice and reproducibility

Formation mechanisms of striations in a filamentary dielectric barrier discharge in atmospheric pressure argon

Formation mechanisms of striations along the discharge channel of a single-filament dielectric barrier discharge (DBD) in argon at atmospheric pressure are investigated by means of a time-dependent, spatially two-dimensional fluid-Poisson model. The model is applied to a one-sided DBD arrangement with a 1.5 mm gap using a sinusoidal high voltage at the powered metal electrode. The discharge conditions are chosen to mimic experimental conditions for which striations have been observed. It is found that the striations form in both half-periods during the transient glow phase, which follows the streamer breakdown phase. The modelling results show that the distinct striated structures feature local spatial maxima and minima in charged and excited particle densities, which are more pronounced during the positive polarity. Their formation is explained by a repetitive stepwise ionisation of metastable argon atoms and ionisation of excimers, causing a disturbance of the spatial distribution of charge carriers along the discharge channel. The results emphasise the importance of excited states and stepwise ionisation processes on the formation of repetitive ionisation waves, eventually leading to striations along the discharge channel.Comment: 18 pages, 15 figures, resubmitted to Plasma Sources Science and Technolog

Spatially resolved simulation of a radio frequency driven micro atmospheric pressure plasma jet and its effluent

Radio frequency driven plasma jets are frequently employed as efficient plasma sources for surface modification and other processes at atmospheric pressure. The radio-frequency driven micro atmospheric pressure plasma jet ($\mu$APPJ) is a particular variant of that concept whose geometry allows direct optical access. In this work, the characteristics of the $\mu$APPJ operated with a helium-oxygen mixture and its interaction with a helium environment are studied by numerical simulation. The density and temperature of the electrons, as well as the concentration of all reactive species are studied both in the jet itself and in its effluent. It is found that the effluent is essentially free of charge carriers but contains a substantial amount of activated oxygen (O, O$_3$ and O$_2(^1\Delta)$). The simulation results are verified by comparison with experimental data

Small-volume resuscitation with hyperoncotic albumin: a systematic review of randomized clinical trials

Background Small-volume resuscitation can rapidly correct hypovolemia. Hyperoncotic albumin solutions, long in clinical use, are suitable for small-volume resuscitation; however, their clinical benefits remain uncertain. Methods Randomized clinical trials comparing hyperoncotic albumin with a control regimen for volume expansion were sought by multiple methods, including computer searches of bibliographic databases, perusal of reference lists, and manual searching. Major findings were qualitatively summarized. In addition, a quantitative meta-analysis was performed on available survival data. Results In all, 25 randomized clinical trials with a total of 1,485 patients were included. In surgery, hyperoncotic albumin preserved renal function and reduced intestinal edema compared with control fluids. In trauma and sepsis, cardiac index and oxygenation were higher after administration of hydroxyethyl starch than hyperoncotic albumin. Improved treatment response and renal function, shorter hospital stay and lower costs of care were reported in patients with liver disease receiving hyperoncotic albumin. Edema and morbidity were decreased in high-risk neonates after hyperoncotic albumin administration. Disability was reduced by therapy with hyperoncotic albumin in brain injury. There was no evidence of deleterious effects attributable to hyperoncotic albumin. Survival was unaffected by hyperoncotic albumin (pooled relative risk, 0.95; 95% confidence interval 0.78 to 1.17). Conclusion In some clinical indications, randomized trial evidence has suggested certain benefits of hyperoncotic albumin such as reductions in morbidity, renal impairment and edema. However, further clinical trials are needed, particularly in surgery, trauma and sepsis