M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: González, B., Calvar, N., Gómez, E., & Domínguez, Á. (2007). Density, dynamic viscosity, and derived properties of binary mixtures of methanol or ethanol with water, ethyl acetate, and methyl acetate at T=(293.15, 298.15, and 303.15)K. The Journal of Chemical Thermodynamics, 39(12), 1578-1588. doi: 10.1016/j.jct.2007.05.004.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Mikhail, S. Z., & Kimel, W. R. (1961). Densities and Viscosities of Methanol-Water Mixtures. Journal of Chemical & Engineering Data, 6(4), 533-537. doi: 10.1021/je60011a015.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Segur, J. B., & Oberstar, H. E. (1951). Viscosity of Glycerol and Its Aqueous Solutions. Industrial & Engineering Chemistry, 43(9), 2117-2120. doi: 10.1021/ie50501a040.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: D’Errico, G., Ortona, O., Capuano, F., & Vitagliano, V. (2004). Diffusion Coefficients for the Binary System Glycerol + Water at 25 °C. A Velocity Correlation Study. Journal of Chemical & Engineering Data, 49(6), 1665-1670. doi: 10.1021/je049917u.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
D. Holzmüller, V. Zaverkin, J. Kästner, und I. Steinwart. Software, (2022)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2022. arXiv: 2203.09410.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Derlacki, Z. J., Easteal, A. J., Edge, A. V. J., Woolf, L. A., & Roksandic, Z. (1985). Diffusion coefficients of methanol and water and the mutual diffusion coefficient in methanol-water solutions at 278 and 298 K. The Journal of Physical Chemistry, 89(24), 5318-5322. doi: 10.1021/j100270a039.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
V. Zaverkin, D. Holzmüller, I. Steinwart, und J. Kästner. Software, (2021)Related to: V. Zaverkin, D. Holzmüller, I. Steinwart, and J. Kästner, “Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments,” J. Chem. Theory Comput. 17, 6658–6670 (2021). doi: 10.1021/acs.jctc.1c00527.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Cristancho, D., Delgado, D., Martínez, F., Abolghassemi Fakhree, M. A., & Jouyban, A. (2011). Volumetric properties of glycerol + water mixtures at several temperatures and correlation with the Jouyban-Acree model. Revista Colombiana de Ciencias Químico Farmacéuticas, 40. 92-115.
D. Holzmüller, V. Zaverkin, J. Kästner, und I. Steinwart. Software, (2022)Related to: David, Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2022. arXiv: 2203.09410.
D. Holzmüller, V. Zaverkin, J. Kästner, und I. Steinwart. Software, (2023)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
M. Gültig, J. Range, B. Schmitz, und J. Pleiss. Software, (2022)Related to: Gültig, M., Range, J. P., Schmitz, B., & Pleiss, J. (2022). Integration of Simulated and Experimentally Determined Thermophysical Properties of Aqueous Mixtures by ThermoML. Journal of Chemical & Engineering Data,. doi: 10.1021/acs.jced.2c00391.
V. Zaverkin, D. Holzmüller, L. Bonfirraro, und J. Kästner. Dataset, (2023)Related to: Viktor Zaverkin, David Holzmüller, Luca Bonfirraro, Johannes Kästner. Transfer learning for chemically accurate interatomic neural network potentials, Phys. Chem. Chem. Phys., 2023, 25, 5383-5396. doi: 10.1039/D2CP05793J.
X. Xu. Dataset, (2023)Related to: Xu, Xiang, Xi Zhang, Andrei Ruban, Siegfried Schmauder, and Blazej Grabowski. "Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al." Acta Materialia 255 (2023): 118986. doi: 10.1016/j.actamat.2023.118986.
T. Giess, S. Itzigehl, J. Range, J. Bruckner, und J. Pleiss. Dataset, (2022)Related to: Giess T., Itzigehl S., Range J. P., Bruckner J. R., Pleiss J., FAIR and scalable management of small-angle X-ray scattering data, 2023. doi: 10.1107/S1600576723001577.
A. Singha Hazari, S. Chandra, Q. Song, D. Hunger, N. Neuman, J. Slageren, E. Klemm, B. Sarkar, und S. Kar. Dataset, (2024)Related to: Chandra, S., Singha Hazari, A., Song, Q., Hunger, D., Neuman, N. I., van Slageren, J., Klemm, E. & Sarkar, B. (2023). Remarkable Enhancement of Catalytic Activity of Cu-Complexes in the Electrochemical Hydrogen Evolution Reaction by Using Triply Fused Porphyrin. ChemSusChem 16, e202201146. doi: 10.1002/cssc.202201146.
K. Abitaev, Y. Qawasmi, P. Atanasova, C. Dargel, T. Hellweg, und T. Sottmann. Dataset, (2024)Related to: Abitaev, Karina; Qawasmi, Yaseen; Atanasova, Petia; Dargel, Carina; Bill, Joachim; Hellweg, Thomas; Sottmann, Thomas: Adjustable polystyrene nanoparticle templates for the production of mesoporous foams and ZnO inverse opals. In: Colloid and Polymer Science 299 (2021), 243-258. doi: 10.1007/s00396-020-04791-5.
K. Endo, A. Raza, L. Yao, S. Gele, A. Rodríguez-Camargo, H. Vignolo-González, L. Grunenberg, und B. Lotsch. Dataset, (2024)Related to: K. Endo, A. Raza, L. Yao, S. Van Gele, A. Rodríguez-Camargo, H. A. Vignolo-González, L. Grunenberg, B. V. Lotsch, Downsizing Porphyrin Covalent Organic Framework Particles Using Protected Precursors for Electrocatalytic CO2 Reduction. Adv. Mater. 2024, 2313197. doi: 10.1002/adma.202313197.
M. Buchmeiser, D. Wang, R. Schowner, L. Stöhr, F. Ziegler, S. Sen, und W. Frey. Dataset, (2024)Related to: M. R. Buchmeiser, D. Wang, R. Schowner, L. Stöhr, F. Ziegler, S. Sen, W. Frey,; Synthetic and Structural Peculiarities of Neutral and Cationic Molybdenum Imido and Tungsten Oxo Alkylidene Complexes Bearing Weakly Coordinating N-Heterocyclic Carbenes; Eur. J. Inorg. Chem., in press (2024). doi: 10.1002/ejic.202400082.
P. Probst, J. Groos, D. Wang, K. Gugeler, A. Beck, J. Kästner, W. Frey, und M. Buchmeiser. Dataset, (2024)Related to: Patrick Probst, Jonas Groos, Dongren Wang, Alexander Beck, Katrin Gugeler, Johannes Kästner, Wolfgang Frey, and Michael R. Buchmeiser, Stereoselective Ring Expansion Metathesis Polymerization with Cationic Molybdenum Alkylidyne N-Heterocyclic Carbene Complexes, Journal of the American Chemical Society 2024 146 (12), 8435-8446. doi: 10.1021/jacs.3c14457.