NeuralMPCX: A Model Predictive Control library that supports classic MPC and neural MPC with CasADi

Lopes-Júnior, Ênio; Reinecke, Sebastian Felix

NeuralMPCX is a Python library for building and deploying Model Predictive Controllers with classic and neural dynamical models. You write constrained MPC with RNN/LSTM models in a CasADi/IPOPT workflow. The library handles CasADi RNN integration, warm-starting, constraint management, real-time...

1 more version(s) exist for this record

Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems

Tahmasbi, Hossein; Knüpfer, Andreas; Kühne, Thomas Dae-Song; Mir Hosseini, Seyed Hossein

Reference data and scripts generated for the "Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems" manuscript.

Data publication: Accelerated free energy estimation in ab initio path integral Monte Carlo simulations

Svensson, Pontus; Kalkavouras, Fotios; Hernandez Acosta, Uwe; Moldabekov, Zhandos; Tolias, Panagiotis; Vorberger, Jan; Dornheim, Tobias

This repository contains the PIMC data for the publication "Accelerated free energy estimation in ab initio path integral Monte Carlo simulations".

Data publication: Towards Non-van der Waals 2D Topological Insulators

Lokamani, Mani; Bihlmayer, Gustav; Michalicek, Gregor; Wortmann, Daniel; Blügel, Stefan; Friedrich, Rico

This dataset includes the primary research data for the publication "Towards Non-van der Waals 2D Topological Insulators"

Multiphase Python Repository by HZDR

Schlegel, Fabian; Fombonne, Clement; Hänsch, Susann; Krull, Benjamin; Lehnigk, Ronald; Meller, Richard

The multiphasepy package is a Python toolkit for building, running, and maintaining CFD simulation case collections for the software released by the OpenFOAM Foundation (but also others, like Ansys Fluent or Siemens Simcenter Star-CCM). It combines reusable library modules with practical...

54 more version(s) exist for this record

Data for Upscaling mineralogy with hyperspectral data: a benchmark dataset and machine learning framework to enable hyperspectral geometallurgy

Thiele, Samuel Thomas; Kirsch, Moritz; Frenzel, Max; Tolosana Delgado, Raimon; Kamath, Akshay Vijay; Guy, Bradley Martin; Kim, Yongwhi; Laura, Tusa; Járóka, Tom; Gloaguen, Richard

Mineral liberation analysis (MLA) dataset accompanying the paper: Upscaling mineralogy with hyperspectral data: a benchmark dataset and machine learning framework to enable hyperspectral geometallurgy. This describes the mineralogy of 204 thick-sections prepared from 49 drillholes sampled across...

Temperature dependence of the dynamic structure factor of the electron liquid via analytic continuation

Chuna, Thomas; Boehme, Maximilian; Dornheim, Tobias

All results have been computed for the unpolarized UEG, i.e., with an equal number of spin-up and spin-down electrons $N^\uparrow=N^\downarrow=N/2$ for $N=34$. For $r_s = 20$ and at $\Theta=0.75$, there are 1000 independent MCMC seeds, at $\Theta=1, \, 2$ there are $280$ seeds, at $\Theta=4,...

QuantumElectrodynamics.jl

Hernandez Acosta, Uwe; Reinhard, Anton; Ehrig, Simeon; Steiniger, Klaus; Bussmann, Michael

QuantumElectrodynamics.jl is an open-source Julia framework to model and simulate interactions between particle and strong electromagnetic fields.

Data publication: Bubble-induced versus thermodynamic voltage losses during pressurized alkaline water electrolysis

Rox, Hannes; Liang, Feng; Baumann, Robert; Marzec, Mateusz M.; Sokołowski, Krystian; Yang, Xuegeng; Lasagni, Andrés F.; van de Krol, Roel; Eckert, Kerstin

Understanding how bubbles influence the efficiency of water electrolysis is crucial to achieve economically competitive hydrogen, generated by renewable energy sources, such as wind and solar power. Water electrolysis is typically performed at high pressures to  lower the cost of the...

Data publication: Titanium Carbide MXene Synthesis by Etching of Titanium Aluminum Carbide in Acetic Acid Solution

Gurzeda, Bartosz Piotr; Boulanger, Nicolas; Li, Gui; Jørgensen, Mads Ry Vogel; Kantor, Innokenty; Baburin, Igor; Petre, Marta; Enachescu, Marius; Talyzin, Alexandr V.

The dataset contains the characterization of the synthesized Ti3C2Tz MXene materials by etching Ti3AlC2 titanium aluminum carbide in solution of ammonium fluoride in acetic acid by XRD, TGA, and XPS.