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1 to 10 of 24 Results
Jan 9, 2024 - Institute of Biochemistry and Technical Biochemistry
Häussler, Max, 2024, "Data for: 'EnzymeML-based modeling workflow: from raw data to kinetic parameters'", https://doi.org/10.18419/darus-3867, DaRUS, V1
Kinetic parameter estimates for small laccase (SLAC) catalyzed oxidation of ABTS, investigated across the temperature range between 25 °C and 45°C. This dataset contains the following files: Unprocessed absorption data from the respective enzyme assays (.txt) Derived calibration...
Dec 14, 2023 - Materials Design
Jung, Jong Hyun; Forslund, Axel; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition", https://doi.org/10.18419/darus-3582, DaRUS, V1, UNF:6:PcXLVWUQ0T4geRQy0F0sgg== [fileUNF]
Data for the publication, Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition, Phys. Rev. B 108, 184107 (2023). This data set contains 1) - the training sets (VASP files), - the low moment-tensor-potentia...
Nov 10, 2023 - SFB 1333 A1+B2 - Buchmeiser group, IPOC-MSF
Ziegler, Felix; Bruckner, Johanna R.; Nowakowski, Michal; Bauer, Matthias; Probst, Patrick; Atwi, Boshra; Buchmeiser, Michael, 2023, "Replication data of the Buchmeiser Group for "Macrocyclization of Dienes Under Confinement With Cationic Tungsten Imido/Oxo Alkylidene N-Heterocyclic Carbene Complexes"", https://doi.org/10.18419/darus-3702, DaRUS, V1
This dataset includes proton nuclear magnetic resonance data from catalytic investigations, scanning electron microscopy images of the ordered mesoporous silica particles, gas adsorption data for the determination of porous diameter, as well as x-ray absorption spectroscopic data...
Oct 5, 2023 - SFB 1333 A1+B2 - Buchmeiser group, IPOC-MSF
Kundu, Koushani; Buchmeiser, Michael, 2023, "Replication Data for Neutral and Cationic Molybdenum Imido Alkylidene Cyclic Alkyl Amino Carbene (CAAC) Complexes for Olefin Metathesis", https://doi.org/10.18419/darus-3697, DaRUS, V1
The files include the NMR data of the novel complexes and cif files of the single crystal X-ray structure of selected structures. Experimental details could be found in the supporting information of the related paper
Jul 27, 2023 - SFB 1333 - Naumann group, IPOC-MSF
Walther, Patrick; Krauß, Annabelle; Naumann, Stefan, 2023, "Data for "Lewis Pair Polymerization of Epoxides via Zwitterionic Species as a Route to High‐Molar‐Mass Polyethers"", https://doi.org/10.18419/darus-1817, DaRUS, V1
A dual catalytic setup based on N‐heterocyclic olefins (NHOs) and magnesium bis(hexamethyldisilazide) (Mg(HMDS)2) was used to prepare poly(propylene oxide) with a molar mass (Mn) >500 000 g mol-1, in some cases even >106 g mol-1, as determined by GPC/light scattering. This is ach...
Jul 19, 2023 - SFB 1333 A3 - Lotsch group, MPI-FKF
Emmerling, Sebastian; Ziegler, Felix; Fischer, Felix R.; Schoch, Roland; Bauer, Matthias; Plietker, Bernd; Buchmeiser, Michael; Lotsch, Bettina, 2023, "Replication data for: "Olefin Metathesis in Confinement: Towards Covalent Organic Framework Scaffolds for Increased Macrocyclization Selectivity"", https://doi.org/10.18419/darus-2729, DaRUS, V1
Covalent organic frameworks (COFs) offer vast structural and chemical diversity enabling a wide and growing range of applications. While COFs are well-established as heterogeneous catalysts, so far, their high and ordered porosity has scarcely been utilized to its full potential...
Jul 19, 2023 - SFB 1333 A3 - Lotsch group, MPI-FKF
Emmerling, Sebastian; Schuldt, Robin; Bette, Sebastian; Yao, Liang; Dinnebier, Robert; Kästner, Johannes; Lotsch, Bettina, 2023, "Replication data for: "Interlayer Interactions as Design Tool for Large-Pore COFs"", https://doi.org/10.18419/darus-2728, DaRUS, V1
ABSTRACT: Covalent organic frameworks (COFs) with a pore size beyond 5 nm are still rarely seen in this emerging field. Besides obvious complications like the elaborated synthesis of large linkers with sufficient solubility, more subtle challenges regarding large-pore COF synthes...
May 12, 2023 - Materials Design
Forslund, Axel; Jung, Jong Hyun; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals", https://doi.org/10.18419/darus-3339, DaRUS, V1
Data for the publication Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals, Phys. Rev. B 107, 174309 (2023). This data set contains - the training sets (VAS...
Jan 11, 2023 - Materials Design
Jung, Jong Hyun; Srinivasan, Prashanth; Forslund, Axel; Grabowski, Blazej, 2023, "Data for: High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials", https://doi.org/10.18419/darus-3239, DaRUS, V1
Data for the publication High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials, npj Comput. Mater., DOI: 10.1038/s41524-022-00956-8 (2023) This data set contains - the training sets (VASP files), - the low mom...
Aug 27, 2022 - SFB 1333 C1 - Dyballa group, ITC
Rieg, Carolin; Dittmann, Daniel; Li, Zheng; Kurtz, Alan; Kaya, Elif; Peters, Stefan; Kunkel, Benny; Parlinska-Wojtan, Magdalena; Wohlrab, Sebastian; Abdel-Mageed, Ali; Dyballa, Michael, 2022, "Publication data of Dyballa group for: "Introducing a Novel Method for Probing Accessibility, Local Environment and Spatial Distribution of Oxidative Sites on Solid Catalysts using Trimethylphosphine"", https://doi.org/10.18419/darus-2992, DaRUS, V1
Primary data files of measurements and processed data of the journal article mentioned under related publications from Dyballa group can be found here. This comprises MAS-NMR, ICP-OES, N2-Physisorption (Brunauer-Emmett-Teller method; BET), XRD, and STEM data. The STEM images are...
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