98 citations · 663 across the 36 of their papers we have counts for
37 papers
From Processing to Functionality: Engineering Accessible Material States in Cu-Embedded SiO Memristive Devices
Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla +5
Resistive switching in oxide-based devices is widely governed by stochastic defect processes, yet a predictive link between fabrication conditions and functional behavior remains e…
On the physical origins of switching diversity in Cu-embedded SiO memristive devices
Sahitya Yarragolla, Rouven Lamprecht, Tobias Gergs +4
Resistive switching devices with sub-stoichiometric SiO and pancake-like Cu nanoparticles (Cu-PCs) exhibit distinct macroscopic current-voltage characteristics classified as ca…
A physics-informed neural network approach to solve the spatially inhomogeneous electron Boltzmann equation
Ihda Chaerony Siffa, Detlef Loffhagen, Markus M. Becker +1
The accurate determination of electron properties is fundamental to low-temperature plasma simulations, necessitating precise solutions to the spatially inhomogeneous electron Bolt…
Wedge-type engineered analog SiO/Cu/SiO-Memristive Devices for Neuromorphic Applications
Rouven Lamprecht, Luca Vialetto, Tobias Gergs +4
This study presents a comprehensive examination of the development of TiN/SiO/Cu/SiO/TiN memristive devices, engineered for neuromorphic applications usin…
Physics-based Modeling and Simulation of Nanoparticle Networks
Torben Hemke, Robin Struck, Sahitya Yarragolla +3
This study presents the computational modeling and simulation of silver nanoparticle networks (NPNs), which, in the realm of neuromorphic computation, suggest to be a promising can…
Nonlinear behavior of memristive devices for hardware security primitives and neuromorphic computing systems
Sahitya Yarragolla, Torben Hemke, Fares Jalled +4
Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonline…
Coexistence of resistive capacitive and virtual inductive effects in memristive devices
Sahitya Yarragolla, Torben Hemke, Jan Trieschmann +1
This paper examines the coexistence of resistive, capacitive, and inertia (virtual inductive) effects in memristive devices, focusing on ReRAM devices, specifically the interface-t…
Non-zero crossing current-voltage characteristics of interface-type resistive switching devices
Sahitya Yarragolla, Torben Hemke, Jan Trieschmann +1
A number of memristive devices, mainly ReRAMs, have been reported to exhibit a unique non-zero crossing hysteresis attributed to the interplay of resistive and not yet fully unders…
Machine learning for advancing low-temperature plasma modeling and simulation
Jan Trieschmann, Luca Vialetto, Tobias Gergs
Machine learning has had an enormous impact in many scientific disciplines. Also in the field of low-temperature plasma modeling and simulation it has attracted significant interes…
PECVD and PEALD on polymer substrates (Part II): Understanding and tuning of barrier and membrane properties of thin films
Teresa de los Arcos, Peter Awakowicz, Marc Böke +19
This feature article presents insights concerning the correlation of PECVD and PEALD thin film structures with their barrier or membrane properties. While in principle similar prec…
PECVD and PEALD on polymer substrates (part I): Fundamentals and analysis of plasma activation and thin film growth
Teresa de los Arcos, Peter Awakowicz, Jan Benedikt +17
This feature article considers the analysis of the initial states of film growth on polymer substrates. The assembled results are based on the cooperation between research groups i…
Towards a Machine-Learned Poisson Solver for Low-Temperature Plasma Simulations in Complex Geometries
Ihda Chaerony Siffa, Markus M. Becker, Klaus-Dieter Weltmann +1
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 solve…
Physics-separating artificial neural networks for predicting sputtering and thin film deposition of AlN in Ar/N discharges on experimental timescales
Tobias Gergs, Thomas Mussenbrock, Jan Trieschmann
Understanding and modeling plasma-surface interactions frame a multi-scale as well as multi-physics problem. Scale-bridging machine learning surface surrogate models have been demo…
Physics-separating artificial neural networks for predicting initial stages of Al sputtering and thin film deposition in Ar plasma discharges
Tobias Gergs, Thomas Mussenbrock, Jan Trieschmann
Simulations of Al thin film sputter depositions rely on accurate plasma and surface interaction models. Establishing the latter commonly requires a higher level of abstraction and…
Charge-optimized many-body interaction potential for AlN revisited to explore plasma-surface interactions
Tobias Gergs, Thomas Mussenbrock, Jan Trieschmann
Plasma-surface interactions during AlN thin film sputter deposition could be studied by means of reactive molecular dynamics (RMD) methods. This requires an interaction potential t…
2022 Review of Data-Driven Plasma Science
Rushil Anirudh, Rick Archibald, M. Salman Asif +60
Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data…
Stochastic behaviour of an interface-based memristive device
Sahitya Yarragolla, Torben Hemke, Jan Trieschmann +3
A large number of simulation models have been proposed over the years to mimic the electrical behaviour of memristive devices. The models are based either on sophisticated mathemat…
Molecular Dynamics Study on the Role of Ar Ions in the Sputter Deposition of Al Thin Films
Tobias Gergs, Thomas Mussenbrock, Jan Trieschmann
Molecular dynamics simulations are often used to study sputtering and thin film growth. Compressive stresses in these thin films are generally assumed to be caused by a combination…
An efficient plasma-surface interaction surrogate model for sputtering processes based on autoencoder neural networks
Tobias Gergs, Borislav Borislavov, Jan Trieschmann
Simulations of thin film sputter deposition require the separation of the plasma and material transport in the gas-phase from the growth/sputtering processes at the bounding surfac…
Kinetic simulation of electron cyclotron resonance assisted gas breakdown in split-biased waveguides for ITER collective Thomson scattering diagnostic
Jan Trieschmann, Axel Wright Larsen, Thomas Mussenbrock +1
For the measurement of the dynamics of fusion-born alpha particles MeV in ITER using collective Thomson scattering (CTS), safe transmission of a gyrotron beam at mm-w…
Ion dynamics in capacitively coupled argon-xenon discharges
M. Klich, S. Wilczek, J. F. J. Janssen +3
An argon-xenon (Ar/Xe) plasma is used as a model system for complex plasmas. Based on this system, symmetric low-pressure capacitively coupled radio-frequency discharges are examin…
Generalized Method for Charge Transfer Equilibration in Reactive Molecular Dynamics
Tobias Gergs, Frederik Schmidt, Thomas Mussenbrock +1
Variable charge models (e.g., EEM, QEq, ES+) in reactive molecular dynamics simulations often inherently impose a global charge transfer between atoms (approximating each system as…
A generic method for equipping arbitrary rf discharge simulation frameworks with external lumped element circuits
Frederik Schmidt, Jan Trieschmann, Tobias Gergs +1
External electric circuits attached to radio-frequency plasma discharges are essential for the power transfer into the discharge and are, therefore, a key element for plasma operat…
Machine learning plasma-surface interface for coupling sputtering and gas-phase transport simulations
Florian Krüger, Tobias Gergs, Jan Trieschmann
Thin film processing by means of sputter deposition inherently depends on the interaction of energetic particles with a target surface and the subsequent particle transport. The le…