| Exploring the Composition Space of High-Entropy Alloy Nanoparticles for the Electrocatalytic H2/CO Oxidation with Bayesian Optimization VA Mints, JK Pedersen, A Bagger, J Quinson, AS Anker, KMØ Jensen, ... ACS Catalysis 12 (18), 11263-11271, 2022 | 30 | 2022 |
| Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis AS Anker, TL Christiansen, M Weber, M Schmiele, E Brok, ETS Kjær, ... Angewandte Chemie 60, 20407–20416, 2021 | 29 | 2021 |
| Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning AS Anker, ETS Kjær, M Juelsholt, TL Christiansen, SL Skjærvø, ... npj Computational Materials 8 (1), 213, 2022 | 25 | 2022 |
| Size-induced amorphous structure in tungsten oxide nanoparticles M Juelsholt, AS Anker, TL Christiansen, MRV Jørgensen, I Kantor, ... Nanoscale 13 (47), 20144-20156, 2021 | 16 | 2021 |
| Formation and growth mechanism for niobium oxide nanoparticles: atomistic insight from in situ X-ray total scattering O Aalling-Frederiksen, M Juelsholt, AS Anker, KMØ Jensen Nanoscale 13 (17), 8087-8097, 2021 | 15 | 2021 |
| Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry AS Anker, KT Butler, R Selvan, KMØ Jensen Chemical Science 14 (48), 14003-14019, 2023 | 14 | 2023 |
| DeepStruc: Towards structure solution from pair distribution function data using deep generative models ETS Kjær, AS Anker, MN Weng, SJL Billinge, R Selvan, KMØ Jensen Digital Discovery 2 (1), 69-80, 2023 | 13 | 2023 |
| Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO 2 NPL Magnard, AS Anker, O Aalling-Frederiksen, A Kirsch, KMØ Jensen Dalton Transactions 51 (45), 17150-17161, 2022 | 12 | 2022 |
| Characterising the atomic structure of mono-metallic nanoparticles from x-ray scattering data using conditional generative models AS Anker, ETS Kjær, EB Dam, SJL Billinge, KMØ Jensen, R Selvan 16th international workshop on mining and learning with graphs under KDD2020 …, 2020 | 11* | 2020 |
| Breaking with the principles of coreduction to form stoichiometric intermetallic PdCu nanoparticles JK Mathiesen, ED Bøjesen, JK Pedersen, ETS Kjær, M Juelsholt, ... Small Methods 6 (6), 2200420, 2022 | 8 | 2022 |
| We are never ever getting (back to) ideal symmetry: structure and luminescence in a ten-coordinated europium (iii) sulfate crystal MS Thomsen, AS Anker, L Kacenauskaite, TJ Sørensen Dalton Transactions 51 (23), 8960-8963, 2022 | 8 | 2022 |
| A simple setup miniaturisation with multiple benefits for Green Chemistry in nanoparticle synthesis JQ Jette Mathiesen, Susan Cooper, Andy Anker, Tiffany Kinnibrugh, Kirsten Jensen ACS Omega 5, 4714–4721, 2022 | 7* | 2022 |
| Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data AS Anker, KT Butler, MD Le, TG Perring, J Thiyagalingam Digital Discovery 2 (3), 578-590, 2023 | 6 | 2023 |
| A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation FL Johansen, AS Anker, U Friis-Jensen, EB Dam, KMØ Jensen, R Selvan | 3 | 2023 |
| POMFinder: identifying polyoxometallate cluster structures from pair distribution function data using explainable machine learning AS Anker, ETS Kjær, M Juelsholt, KM Jensen Journal of Applied Crystallography 57 (1), 2024 | 2 | 2024 |
| Atomic structural changes in the formation of transition metal tungstates: the role of polyoxometalate structures in material crystallization SL Skjærvø, AS Anker, MC Wied, ETS Kjær, M Juelsholt, TL Christiansen, ... Chemical Science 14 (18), 4806-4816, 2023 | 2 | 2023 |
| CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning U Friis-Jensen, FL Johansen, AS Anker, EB Dam, KMØ Jensen, R Selvan Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 1 | 2024 |
| ClusterFinder: a fast tool to find cluster structures from pair distribution function data AS Anker, U Friis-Jensen, FL Johansen, SJL Billinge, KM Jensen Acta Crystallographica Section A: Foundations and Advances 80 (2), 2024 | 1 | 2024 |
| MLstructureMining: a machine learning tool for structure identification from X-ray pair distribution functions ETS Kjær, AS Anker, A Kirsch, J Lajer, O Aalling-Frederiksen, SJL Billinge, ... Digital Discovery 3 (5), 908-918, 2024 | 1 | 2024 |
| Following structural changes in iridium nanoparticles during oxygen evolution electrocatalysis with operando X-ray total scattering R Pittkowski, S Punke, AS Anker, A Bornet, N Magnard, N Schlegel, ... | 1 | 2023 |
Kirsten Marie Ørnsbjerg JensenUniversity of CopenhagenVerified email at chem.ku.dk
