Journal Article (101)

2024
Journal Article
Miyazaki, R.; Belthle, K. S.; Tüysüz, H.; Foppa, L.; Scheffler, M.: Materials Genes of CO2 Hydrogenation on Supported Cobalt Catalysts: An Artificial Intelligence Approach Integrating Theoretical and Experimental Data. Journal of the American Chemical Society 146 (8), pp. 5433 - 5444 (2024)
Journal Article
Yin, J.; Rao, Z.; Wu, D.; Lv, H.; Ma, H.; Long, T.; Kang, J.; Wang, Q.; Wang, Y.; Su, R.: Interpretable Predicting Creep Rupture Life of Superalloys: Enhanced by Domain-Specific Knowledge. Advanced Science 11 (11), 2307982 (2024)
2023
Journal Article
Duc Pham, L. V.; Sattler, P.; Marques, M. A. L.; Benavides-Riveros, C. L.: Homogeneous electron liquid in arbitrary dimensions beyond the random phase approximation. New Journal of Physics 25, 083040 (2023)
Journal Article
Katnagallu, S.; Freysoldt, C.; Gault, B.; Neugebauer, J.: Ab initio vacancy formation energies and kinetics at metal surfaces under high electric field. Physical Review B 107 (4), L041406 (2023)
Journal Article
Kaygisiz, K.; Dutta, A.; Rauch-Wirth, L.; Synatschke, C. V.; Münch, J.; Bereau, T.; Weil, T.: Inverse design of viral infectivity-enhancing peptide fibrils from continuous protein-vector embeddings. Biomaterials Science 11 (15), pp. 5251 - 5261 (2023)
Journal Article
Kaygisiz, K.; Rauch-Wirth, L.; Dutta, A.; Yu, X.; Nagata, Y.; Bereau, T.; Münch, J.; Synatschke, C. V.; Weil, T.: Data-mining unveils structure-property-activity correlation of viral infectivity enhancing self-assembling peptides. Nature Communications 14, 5121 (2023)
Journal Article
Khorrami, M. S.; Mianroodi, J. R.; Siboni, N. H.; Goyal, P. K.; Svendsen, B.; Benner, P.; Raabe, D.: An Artificial Neural Network for Surrogate Modeling of Stress Fields in Viscoplastic Polycrystalline Materials. npj Computational Materials 9, 37 (2023)
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Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: Anharmonicity in Thermal Insulators: An Analysis from First Principles. Physical Review Letters 130 (23), 236301 (2023)
Journal Article
Kour, K.; Dolgov, S.; Stoll, M.; Benner, P.: Efficient Structure-preserving Support Tensor Train Machine. Journal of Machine Learning Research 24 (4), pp. 1 - 22 (2023)
Journal Article
Kusampudi, N.; Diehl, M.: Inverse design of dual-phase steel microstructures using generative machine learning model and Bayesian optimization. International Journal of Plasticity 171, 103776 (2023)
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Leitherer, A.; Yeo, B. C.; Liebscher, C. H.; Ghiringhelli, L. M.: Automatic identification of crystal structures and interfaces via artificial-intelligence-based electron microscopy. npj Computational Materials 9, 179 (2023)
Journal Article
Li, Y.; Wei, Y.; Wang, Z.; Liu, X.; Colnaghi, T.; Han, L.; Rao, Z.; Zhou, X.; Huber, L.; Dsouza, R. et al.; Gong, Y.; Neugebauer, J.; Marek, A.; Rampp, M.; Bauer, S.; Li, H.; Baker, I.; Stephenson, L.; Gault, B.: Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography. Nature Communications 14 (1), 7410 (2023)
Journal Article
Pincelli, T.; Vasileiadis, T.; Dong, S.; Beaulieu, S.; Dendzik, M. R.; Zahn, D.; Lee, S.-E.; Seiler, H.; Qi, Y.; Xian, R. P. et al.; Maklar, J.; Coy, E.; Mueller, N. S.; Okamura, Y.; Reich, S.; Wolf, M.; Rettig, L.; Ernstorfer, R.: Observation of Multi-Directional Energy Transfer in a Hybrid Plasmonic–Excitonic Nanostructure. Advanced Materials 35 (9), 2209100 (2023)
Journal Article
Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.: Recent advances in the SISSO method and their implementation in the SISSO++ Code. The Journal of Chemical Physics 159 (11), 114110 (2023)
Journal Article
Rao, Z.; Li, Y.; Zhang, H.; Colnaghi, T.; Marek, A.; Rampp, M.; Gault, B.: Direct recognition of crystal structures via three-dimensional convolutional neural networks with high accuracy and tolerance to random displacements and missing atoms. Scripta Materialia 234, 115542 (2023)
Journal Article
Saxena, A.; Polin, N.; Kusampudi, N.; Katnagallu, S.; Molina-Luna, L.; Gutfleisch, O.; Berkels, B.; Gault, B.; Neugebauer, J.; Freysoldt, C.: A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data. Microscopy and Microanalysis 29 (5), pp. 1658 - 1670 (2023)
Journal Article
Scheidgen, M.; Himanen , L.; Ladines, A. N.; Sikter, D.; Nakhaee, M.; Fekete, A.; Chang, T.; Golparvar, A.; Márquez, J. A.; Brockhauser, S. et al.; Brückner , S.; Ghiringhelli, L. M.; Dietrich, F.; Lehmberg, D.; Denell, T.; Albino, A.; Näsström, H.; Shabih, S.; Dobener, F.; Kühbach, M.; Mozumder, R.; Rudzinski, J. F.; Daelman, N.; Pizarro, J. M.; Kuban, M.; Salazar, C.; Ondračka, P.; Bungartz, H.-J.; Draxl, C.: NOMAD: A distributed web-based platform for managing materials science research data. The Journal of Open Source Software (JOSS) 8 (90), 5388 (2023)
Journal Article
Xian, R. P.; Stimper, V.; Zacharias, M.; Dendzik, M. R.; Dong, S.; Beaulieu, S.; Schölkopf, B.; Wolf, M.; Rettig, L.; Carbogno, C. et al.; Bauer, S.; Ernstorfer, R.: A machine learning route between band mapping and band structure. Nature Computational Science 3 (1), pp. 101 - 114 (2023)
2022
Journal Article
Benavides-Riveros, C. L.; Chen, L.; Schilling, C.; Mantilla, S.; Pitallis, S.: Excitations of Quantum Many-Body Systems via Purified Ensembles: A Unitary-Coupled-Cluster-Based Approach. Physical Review Letters 129 (6), 066401 (2022)
Journal Article
Bowker, M.; DeBeer, S.; Dummer, N. F.; Hutchings, G. J.; Scheffler, M.; Schüth, F.; Taylor, S. H.; Tüysüz, H.: Advancing Critical Chemical Processes for a Sustainable Future: Challenges for Industry and the Max Planck–Cardiff Centre on the Fundamentals of Heterogeneous Catalysis (FUNCAT). Angewandte Chemie International Edition 61 (50), e202209016 (2022)
Journal Article
Cautaerts, N.; Crout, P.; Ånes, H. W.; Prestat, E.; Jeong, J.; Dehm, G.; Liebscher, C.: Free, flexible and fast: Orientation mapping using the multi-core and GPU-accelerated template matching capabilities in the Python-based open source 4D-STEM analysis toolbox Pyxem. Ultramicroscopy 237, 113517 (2022)
Journal Article
Dutta, A.; Bereau, T.; Vilgis, T. A.: Identifying Sequential Residue Patterns in Bitter and Umami Peptides. ACS Food Science & Technology 2 (11), pp. 1773 - 1780 (2022)
Journal Article
Gedeon, J.; Schmidt, J.; Hodgson, M. J. P.; Wetherell, J.; Benavides-Riveros, C. L.; Marques, M. A. L.: Machine learning the derivative discontinuity of density-functional theory. Machine Learning: Science and Technology 3 (1), 015011 (2022)
Journal Article
Goyal, P. K.; Benner, P.: Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression Approach. Proceedings of the Royal Society A 478 (2262), 20210883 (2022)
Journal Article
Kuban, M.; Gabaj, Š.; Aggoune, W.; Vona, C.; Rigamonti, S.; Draxl, C.: Similarity of materials and data-quality assessment by fingerprinting. MRS Bulletin 47, pp. 991 - 999 (2022)
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