TY - JOUR A1 - Anker, Andy S. A1 - Aspuru-Guzik, Alán A1 - Ben Mahmoud, Chiheb A1 - Bennett, Sophie A1 - Briling, Ksenia R. A1 - Changiarath, Arya A1 - Chong, Sanggyu A1 - Collins, Christopher M. A1 - Cooper, Andrew I. A1 - Crusius, Daniel A1 - Darmawan, Kevion K. A1 - Das, Basita A1 - David, Nicholas A1 - Day, Graeme M. A1 - Deringer, Volker L. A1 - Duarte, Fernanda A1 - Eardley-Brunt, Annabel A1 - Evans, Matthew L. A1 - Evans, Rob A1 - Fairlamb, Ian A1 - Franklin, Barnabas A. A1 - Frey, Jeremy A1 - Ganose, Alex M. A1 - Goulding, Mark A1 - Hafizi, Roohollah A1 - Hakkennes, Matthijs A1 - Hickey, Niamh A1 - James, Gillian A1 - Jelfs, Kim E. A1 - Kalikadien, Adarsh V. A1 - Kapil, Venkat A1 - Koczor-Benda, Zsuzsanna A1 - Krammer, Ferdinand A1 - Kulik, Heather J. A1 - Kumar, Vishank A1 - Kuttner, Christian A1 - Lam, Erwin A1 - Lou, Yuchen A1 - Mante, Eltjo A1 - Martin, Jennie A1 - Mroz, Austin M. A1 - Nematiaram, Tahereh A1 - Pare, Charles W. P. A1 - Patra, Sarbani A1 - Proudfoot, James A1 - Ruscic, Branko A1 - Ryder, Matthew R. A1 - Sakaushi, Ken A1 - Saßmannshausen, Jörg A1 - Savoie, Brett M. A1 - Schneider, Nadine A1 - Schwaller, Philippe A1 - Skjelstad, Bastian Bjerkem A1 - Sun, Wenhao A1 - Szczypiński, Filip T. A1 - Torrisi, Steven A1 - Ueltzen, Katharina A1 - Vishnoi, Shubham A1 - Walsh, Aron A1 - Wang, Xinwei A1 - Wilson, Chloe A1 - Wu, Ruiqi A1 - Zeitler, Jakob T1 - Discovering structure–property correlations: General discussion N2 - This article is a discussion of the paper "Web-BO: Towards increased accessibility of Bayesian optimisation (BO) for chemistry" by Austin M. Mroz, Piotr N. Toka, Ehecatl Antonio del Río Chanona and Kim E. Jelfs (Faraday discussions, 2025, 256, 221-234). KW - Materials design KW - Machine learning KW - Automation KW - Materials discovery PY - 2025 DO - https://doi.org/10.1039/d4fd90062f SN - 1359-6640 SN - 1364-5498 VL - 256 IS - Themed collection: Data-driven discovery in the chemical sciences SP - 373 EP - 412 PB - Royal Society of Chemistry (RSC) CY - Cambridge AN - OPUS4-62208 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Comba, P. A1 - Emmerling, Franziska A1 - Jakob, M. A1 - Kraus, Werner A1 - Kubeil, M. A1 - Morgen, M. A1 - Pietzsch, J. A1 - Stephan, H. T1 - Copper(II) chemistry of the functionalized macrocycle cyclam tetrapropionic acid N2 - The CuII complex of H4TETP (H4TETP = 1,4,8,11-tetraazatetradecane-1,4,8,11-tetrapropionic acid) is five-coordinate with a distorted square-pyramidal structure (τ = 0.45; i.e. the geometry is nearly half-way between square-pyramidal and trigonal-bipyramidal) and a relatively long Cu–N and a short Cu–O bond; the comparison between powder and solution electronic spectroscopy, the frozen solution EPR spectrum and ligand-field-based calculations (angular overlap model, AOM) indicate that the solution and solid state structures are very similar, i.e. the complex has a relatively low 'in-plane' and a significant axial ligand field with a dx²-y² ground state. The ligand-enforced structure is therefore shown to lead to a partially quenched Jahn–Teller distortion and to a relatively low complex stability, lower than with the corresponding acetate-derived ligand H4TETA. This is confirmed by potentiometric titration and by the biodistribution with 64Cu-labeled ligands which show that the uptake in the liver is significantly increased with the H4TETP-based system. KW - Copper(II) KW - Chemistry PY - 2013 DO - https://doi.org/10.1039/c2dt32356g SN - 1477-9226 SN - 1477-9234 SN - 1364-5447 VL - 42 IS - 17 SP - 6142 EP - 6148 PB - RSC CY - Cambridge AN - OPUS4-28075 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Batatia, Ilyes A1 - Benner, Philipp A1 - Chiang, Yuan A1 - Elena, Alin M. A1 - Kovács, Dávid P. A1 - Riebesell, Janosh A1 - Advincula, Xavier R. A1 - Asta, Mark A1 - Avaylon, Matthew A1 - Baldwin, William J. A1 - Berger, Fabian A1 - Bernstein, Noam A1 - Bhowmik, Arghya A1 - Bigi, Filippo A1 - Blau, Samuel M. A1 - Cărare, Vlad A1 - Ceriotti, Michele A1 - Chong, Sanggyu A1 - Darby, James P. A1 - De, Sandip A1 - Della Pia, Flaviano A1 - Deringer, Volker L. A1 - Elijošius, Rokas A1 - El-Machachi, Zakariya A1 - Fako, Edvin A1 - Falcioni, Fabio A1 - Ferrari, Andrea C. A1 - Gardner, John L. A. A1 - Gawkowski, Mikołaj J. A1 - Genreith-Schriever, Annalena A1 - George, Janine A1 - Goodall, Rhys E. A. A1 - Grandel, Jonas A1 - Grey, Clare P. A1 - Grigorev, Petr A1 - Han, Shuang A1 - Handley, Will A1 - Heenen, Hendrik H. A1 - Hermansson, Kersti A1 - Ho, Cheuk Hin A1 - Hofmann, Stephan A1 - Holm, Christian A1 - Jaafar, Jad A1 - Jakob, Konstantin S. A1 - Jung, Hyunwook A1 - Kapil, Venkat A1 - Kaplan, Aaron D. A1 - Karimitari, Nima A1 - Naik, Aakash A. A1 - Csányi, Gábor T1 - A foundation model for atomistic materials chemistry N2 - Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here, we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model—and its qualitative and at times quantitative accuracy—on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces, and even the dynamics of a small protein. The model can be applied out of the box as a starting or “foundation” model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users obtain reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step toward democratizing the revolution in atomic-scale modeling that has been brought about by ML force fields. KW - Materials Design KW - Thermal Conducitivity KW - Nanoparticles KW - Batteries PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-647829 DO - https://doi.org/10.1063/5.0297006 SN - 0021-9606 VL - 163 IS - 18 SP - 1 EP - 89 PB - AIP Publishing AN - OPUS4-64782 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lu, Z. C. A1 - Haist, M. A1 - Ivanov, D. A1 - Jakob, C. A1 - Jansen, D. A1 - Schmid, M. A1 - Kißling, P. A. A1 - Leinitz, Sarah A1 - Link, J. A1 - Mechtcherine, V. A1 - Neubauer, J. A1 - Plank, J. A1 - Schmidt, Wolfram A1 - Schilde, C. A1 - Schröfl, C. A1 - Sowoidnich, T. A1 - Stephan, D. T1 - Characterization data of reference cement CEM III/A 42.5N used for priority program DFG SPP 2005 "Opus Fluidum Futurum - Rheology of reactive, multiscale, multiphase construction materials" N2 - Two types of cements were selected as the reference cement in the priority program 2005 of the German Research Foundation (DFG SPP 2005). A thorough characterization of CEM I 42.5 R has been made in a recent publication. In this paper, the characterization data of the other reference cement CEM III/A 42.5 N are presented from the aspects of chemical and mineralogical compositions as well as physical and chemical properties. The characterization data of the slag, which is the second main constituent of this specific cement besides the clinker, are presented independently. For all data received, the mean values and the corresponding errors were calculated. The data shall be used for the ongoing research within the priority program. Also, researchers from outside this priority program can benefit from these data if the same materials are used. KW - Cement KW - Slag KW - Characterization KW - DFG SPP 2005 PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-568980 DO - https://doi.org/10.1016/j.dib.2020.105524 SN - 2352-3409 VL - 30 SP - 1 EP - 14 PB - Elsevier CY - Amsterdam AN - OPUS4-56898 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pott, U. A1 - Crasselt, Claudia A1 - Fobbe, N. A1 - Haist, M. A1 - Heinemann, M. A1 - Hellmann, S. A1 - Ivanov, D. A1 - Jakob, C. A1 - Jansen, D. A1 - Lei, L. A1 - Li, R. A1 - Link, J. A1 - Lowke, D. A1 - Mechtcherine, V. A1 - Neubauer, J. A1 - Nicia, D. A1 - Plank, J. A1 - Reißig, S. A1 - Schäfer, T. A1 - Schilde, C. A1 - Schmidt, Wolfram A1 - Schröfl, C. A1 - Sowoidnich, T. A1 - Strybny, B. A1 - Ukrainczyk, N. A1 - Wolf, J. A1 - Xiao, P. A1 - Stephan, D. T1 - Characterization data of reference materials used for phase II of the priority program DFG SPP 2005 “Opus Fluidum Futurum –Rheology of reactive, multiscale, multiphase construction materials” N2 - A thorough characterization of base materials is the prereq- uisite for further research. In this paper, the characterization data of the reference materials (CEM I 42.5 R, limestone pow- der, calcined clay and a mixture of these three components) used in the second funding phase of the priority program 2005 of the German Research Foundation (DFG SPP 2005) are presented under the aspects of chemical and min- eralogical composition as well as physical and chemical properties. The data were collected based on tests performed by up to eleven research groups involved in this cooperative program. KW - Portland cement KW - Limestone powder KW - Calcined clay KW - Sustainable cement KW - DFG SPP 2005 PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-569913 DO - https://doi.org/10.1016/j.dib.2023.108902 VL - 47 SP - 1 EP - 19 PB - Elsevier AN - OPUS4-56991 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lu, Z. A1 - Haist, M. A1 - Ivanov, D. A1 - Jakob, C. A1 - Jansen, D. A1 - Leinitz, Sarah A1 - Link, J. A1 - Mechtcherine, V. A1 - Neubauer, J. A1 - Plank, J. A1 - Schmidt, Wolfram A1 - Schilde, C. A1 - Schröfl, C. A1 - Sowoidnich, T. A1 - Stephan, D. T1 - Characterization data of reference cement CEM I 42.5 R used for Priority Program DFG SPP 2005 “Opus Fluidum Futurum - Rheology of reactive, multiscale, multiphase construction materials” N2 - A thorough characterization of starting materials is the precondition for further research, especially for cement, which contains various phases and presents quite a complex material for fundamental scientific investigation. In the paper at hand, the characterization data of the reference cement CEM I 42.5 R used within the priority program 2005 of the German Research Foundation (DFG SPP 2005) are presented from the aspects of chemical and mineralogical compositions as well as physical and chemical properties. The data were collected based on tests conducted by nine research groups involved in this cooperative program. For all data received, the mean values and the corresponding errors were calculated. The results shall be used for the ongoing research within the priority program. KW - Portland cement KW - Characterization KW - DFG SPP 2005 PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-500849 DO - https://doi.org/10.1016/j.dib.2019.104699 SN - 2352-3409 VL - 27 SP - 104699 PB - Elsevier Inc. AN - OPUS4-50084 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schröder, Jakob A1 - Mishurova, Tatiana A1 - Fritsch, Tobias A1 - Serrano-Munoz, Itziar A1 - Evans, Alexander A1 - Sprengel, Maximilian A1 - Klaus, M. A1 - Genzel, C. A1 - Schneider, J. A1 - Bruno, Giovanni T1 - On the influence of heat treatment on microstructure and mechanical behavior of laser powder bed fused Inconel 718 N2 - A range of heat treatments have been developed for wrought Inconel 718 to obtain desired properties. For additively manufactured Inconel 718, the recently developed standard ASTM F3301 provides guidance for heat treatment of powder bed fusion specimens. Although this standard is based on standards developed for wrought Inconel 718, it does not include direct aging. Since direct aging reduces the number of processing steps, it can result in a post processing cost reduction if the desired properties are obtained. In this study, we characterized the microstructure and tensile behavior of Inconel 718 specimens produced by a laser powder bed fusion process. The specimens were heat treated according to two different routines after stress relieving: a full heat Treatment versus a one-step direct aging process. Differences in the resulting texture and grain morphology were observed. The ex-situ stress-strain behavior was broadly similar. However, a slight increase in yield strength was observed for the direct aged specimen. In order to understand this behavior, investigations with in-situ synchrotron Energy dispersive X-ray diffraction tensile testing revealed differences in the load partitioning among different Crystal directions. Importantly, the elastic anisotropy expressed by the magnitude of the diffraction elastic constants showed a dependency on the microstructures. KW - Electron microscopy KW - X-ray analysis KW - Inconel 718 KW - Additive Manufacturing KW - Mechanical behavior KW - Diffraction elastic constants PY - 2021 DO - https://doi.org/10.1016/j.msea.2020.140555 VL - 805 SP - 40555 PB - Elsevier B.V. CY - Amsterdam AN - OPUS4-52142 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schröder, Jakob A1 - Heldmann, A. A1 - Hofmann, M. A1 - Evans, Alexander A1 - Petry, W. A1 - Bruno, Giovanni T1 - Determination of diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 N2 - High energy X-ray synchrotron diffraction is used to investigate the elastic anisotropy of the nickel-based superalloy IN718 produced by laser powder bed fusion (PBF-LB). This material is characterized by a columnar grain morphology with some crystallographic texture. The material is subjected to elastic loading to determine the diffraction elastic constants (DECs). Furthermore, the single-crystal elastic constants (SCEC) are refined from these experiments using different micromechanical models. The results show that each micromechanical model predicts a specific set of SCEC that well describes the elastic anisotropy of PBF-LB/IN718. KW - Mechanical Engineering KW - Mechanics of Materials KW - Condensed Matter Physics KW - General Materials Science PY - 2023 DO - https://doi.org/10.1016/j.matlet.2023.135305 SN - 0167-577X VL - 353 SP - 1 EP - 5 PB - Elsevier B.V. AN - OPUS4-58477 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Karafiludis, Stephanos A1 - Standl, Jacob A1 - Ryll, Tom W. A1 - Schwab, Alexander A1 - Prinz, Carsten A1 - Wolf, Jakob B. A1 - Kruschwitz, Sabine A1 - Emmerling, Franziska A1 - Völker, Christoph A1 - Stawski, Tomasz M. T1 - High-Entropy Phosphate Synthesis: Advancements through Automation and Sequential Learning Optimization N2 - Transition metal phosphates (TMPs) are extensively explored for electrochemical and catalytical applications due to their structural versatility and chemical stability. Within this material class, novel high-entropy metal phosphates (HEMPs)─containing multiple transition metals combined into a single-phase structure─are particularly promising, as their compositional complexity can significantly enhance functional properties. However, the discovery of suitable HEMP compositions is hindered by the vast compositional design space and complex or very specific synthesis conditions. Here, we present a data-driven strategy combining automated wet-chemical synthesis with a Sequential Learning App for Materials Discovery (SLAMD) framework (Random Forest regression model) to efficiently explore and optimize HEMP compositions. Using a limited set of initial experiments, we identified multimetal compositions in a single-phase crystalline solid. The model successfully predicted a novel Co0.3Ni0.3Fe0.2Cd0.1Mn0.1 phosphate octahydrate phase, validated experimentally, demonstrating the effectiveness of the machine learning approach. This work highlights the potential of integrating automated synthesis platforms with data-driven algorithms to accelerate the discovery of high-entropy materials, offering an efficient design pathway to advanced functional materials. KW - Metal phosphates KW - High entropy KW - Sequential learning KW - Automated synthesis KW - MAP KW - Random forest KW - Machine learning PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-641554 DO - https://doi.org/10.1021/acs.cgd.5c00549 SN - 1528-7483 VL - 25 IS - 19 SP - 7989 EP - 8001 PB - American Chemical Society (ACS) CY - Washington, DC AN - OPUS4-64155 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -