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Graph neural networks for materials science and chemistry

Abstract (Expand)

Abstract Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, …ns, design new structures, and predict synthesis routes of new materials. Graph neural networks (GNNs) are one of the fastest growing classes of machine learning models. They are of particular relevance for chemistry and materials science, as they directly work on a graph or structural representation of molecules and materials and therefore have full access to all relevant information required to characterize materials. In this Review, we provide an overview of the basic principles of GNNs, widely used datasets, and state-of-the-art architectures, followed by a discussion of a wide range of recent applications of GNNs in chemistry and materials science, and concluding with a road-map for the further development and application of GNNs.

Authors: Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich

Date Published: 1st Dec 2022

Publication Type: Journal

Improved asteroseismic inversions for red-giant surface rotation rates

Abstract (Expand)

Context: Asteroseismic observations of internal stellar rotation have indicated a substantial lack of angular momentum transport in theoretical models of subgiant and red-giant stars. Accurate core and … surface rotation rate measurements are therefore needed to constrain the internal transport processes included in the models. Aims: We eliminate substantial systematic errors of asteroseismic surface rotation rates found in previous studies. Methods: We propose a new objective function for the optimally localised averages method of rotational inversions for red-giant stars, which results in more accurate envelope rotation rate estimates obtained from the same data. We use synthetic observations from stellar models across a range of evolutionary stages and masses to demonstrate the improvement. Results: We find that our new inversion technique allows us to obtain estimates of the surface rotation rate that are independent of the core rotation. For a star at the base of the red-giant branch, we reduce the systematic error from about 20% to a value close to 0, assuming constant envelope rotation. We also show the equivalence between this method and the method of linearised rotational splittings. Conclusions: Our new rotational inversion method substantially reduces the systematic errors of red-giant surface rotation rates. In combination with independent measures of the surface rotation rate, this will allow better constraints to be set on the internal rotation profile. This will be a very important probe for further constraining the internal angular momentum transport along the lower part of the red-giant branch.

Authors: F. Ahlborn, E. P. Bellinger, S. Hekker, S. Basu, D. Mokrytska

Date Published: 1st Dec 2022

Publication Type: Journal

Companions to Kepler giant stars: A long-period eccentric sub-stellar companion to KIC 3526061 and a stellar companion to HD 187878

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Context: Our knowledge of populations and the occurrence of planets orbiting evolved intermediate-mass stars is still incomplete. In 2010 we started a planet search programme among 95 giant stars … observed by the Kepler mission to increase the sample of giant stars with planets and with reliable estimates of stellar masses and radii. Aims: We present the two systems from our planet search programme whose companions we were able to characterise: KIC 3526061 and HD 187878. Methods: We used precise stellar radial velocity measurements taken with four different echelle spectrographs to derive an orbital solution. We used Gaia astrometric measurements to obtain the inclination of the HD 187878 system and Kepler photometric observations to estimate the stellar mass and radius. Results: We report the discovery of a sub-stellar companion and a stellar companion around two intermediate-mass red giant branch stars. KIC 3526061 b is most likely a brown dwarf with a minimum mass of 18.15 ± 0.44 M Jupiter in a long-period eccentric orbit, with orbital period 3552−135+158d and orbital eccentricity e= 0.85 ± 0.01. It is the most evolved system found having a sub-stellar companion with such a high eccentricity and wide separation. HD 187878 B has a minimum mass of 78.4 ± 2.0 M Jupiter. Combining the spectroscopic orbital parameters with the astrometric proper motion anomaly, we derived an orbital inclination i=9.8−0.6+0.4deg, which corresponds to the companion’s mass in the stellar regime of 0.51−0.02+0.04M⊙. Conclusions: A sub-stellar companion of KIC 3526061 extends the sample of known red giant branch stars with sub-stellar companions on very eccentric wide orbits, and might provide a probe of the dynamical evolution of such systems over time.

Authors: Marie Karjalainen, Raine Karjalainen, Artie P. Hatzes, Holger Lehmann, Pierre Kervella, Saskia Hekker, Hans Van Winckel, Jakub Überlauer, Michaela Vítková, Marek Skarka, Petr Kabáth, Saskia Prins, Andrew Tkachenko, William D. Cochran, Alain Jorissen

Date Published: 1st Dec 2022

Publication Type: Journal

From Easy to Hopeless—Predicting the Difficulty of Phylogenetic Analyses

Abstract (Expand)

Abstract Phylogenetic analyzes under the Maximum-Likelihood (ML) model are time and resource intensive. To adequately capture the vastness of tree space, one needs to infer multiple independent trees. …ultiple independent trees. On some datasets, multiple tree inferences converge to similar tree topologies, on others to multiple, topologically highly distinct yet statistically indistinguishable topologies. At present, no method exists to quantify and predict this behavior. We introduce a method to quantify the degree of difficulty for analyzing a dataset and present Pythia, a Random Forest Regressor that accurately predicts this difficulty. Pythia predicts the degree of difficulty of analyzing a dataset prior to initiating ML-based tree inferences. Pythia can be used to increase user awareness with respect to the amount of signal and uncertainty to be expected in phylogenetic analyzes, and hence inform an appropriate (post-)analysis setup. Further, it can be used to select appropriate search algorithms for easy-, intermediate-, and hard-to-analyze datasets.

Authors: Julia Haag, Dimitri Höhler, Ben Bettisworth, Alexandros Stamatakis

Date Published: 1st Dec 2022

Publication Type: Journal

The VLT-FLAMES Tarantula Survey. Observational evidence for two distinct populations of massive runaway stars in 30 Doradus

Abstract

Not specified

Authors: H. Sana, O. H. Ramı́rez-Agudelo, V. Hénault-Brunet, L. Mahy, L. A. Almeida, A. de Koter, J. M. Bestenlehner, C. J. Evans, N. Langer, F. R. N. Schneider, P. A. Crowther, S. E. de Mink, A. Herrero, D. J. Lennon, M. Gieles, J. Maı́z Apellániz, M. Renzo, E. Sabbi, J. Th. van Loon, J. S. Vink

Date Published: 1st Dec 2022

Publication Type: Journal

Structure and dynamics of the von Willebrand Factor C6 domain

Abstract (Expand)

Von Willebrand disease (VWD) is a bleeding disorder with different levels of severity. VWD-associated mutations are located in the von Willebrand factor (VWF) gene, coding for the large multidomain … plasma protein VWF with essential roles in hemostasis and thrombosis. On the one hand, a variety of mutations in the C-domains of VWF are associated with increased bleeding upon vascular injury. On the other hand, VWF gain-of-function (GOF) mutations in the C4 domain have recently been identified, which induce an increased risk of myocardial infarction. Mechanistic insights into how these mutations affect the molecular behavior of VWF are scarce and holistic approaches are challenging due to the multidomain and multimeric character of this large protein. Here, we determine the structure and dynamics of the C6 domain and the single nucleotide polymorphism (SNP) variant G2705R in C6 by combining nuclear magnetic resonance spectroscopy, molecular dynamics simulations and aggregometry. Our findings indicate that this mutation mostly destabilizes VWF by leading to a more pronounced hinging between both subdomains of C6. Hemostatic parameters of variant G2705R are close to normal under static conditions, but the missense mutation results in a gain-of-function under flow conditions, due to decreased VWF stem stability. Together with the fact that two C4 variants also exhibit GOF characteristics, our data underline the importance of the VWF stem region in VWF’s hemostatic activity and the risk of mutation-associated prothrombotic properties in VWF C-domain variants due to altered stem dynamics.

Authors: Po-Chia Chen, Fabian Kutzki, Angelika Mojzisch, Bernd Simon, Emma-Ruoqi Xu, Camilo Aponte-Santamaría, Kai Horny, Cy Jeffries, Reinhard Schneppenheim, Matthias Wilmanns, Maria A. Brehm, Frauke Gräter, Janosch Hennig

Date Published: 18th Nov 2022

Publication Type: Journal

Horizons: nuclear astrophysics in the 2020s and beyond

Abstract (Expand)

Abstract Nuclear astrophysics is a field at the intersection of nuclear physics and astrophysics, which seeks to understand the nuclear engines of astronomical objects and the origin of the chemical …the origin of the chemical elements. This white paper summarizes progress and status of the field, the new open questions that have emerged, and the tremendous scientific opportunities that have opened up with major advances in capabilities across an ever growing number of disciplines and subfields that need to be integrated. We take a holistic view of the field discussing the unique challenges and opportunities in nuclear astrophysics in regards to science, diversity, education, and the interdisciplinarity and breadth of the field. Clearly nuclear astrophysics is a dynamic field with a bright future that is entering a new era of discovery opportunities.

Authors: H Schatz, A D Becerril Reyes, A Best, E F Brown, K Chatziioannou, K A Chipps, C M Deibel, R Ezzeddine, D K Galloway, C J Hansen, F Herwig, A P Ji, M Lugaro, Z Meisel, D Norman, J S Read, L F Roberts, A Spyrou, I Tews, F X Timmes, C Travaglio, N Vassh, C Abia, P Adsley, S Agarwal, M Aliotta, W Aoki, A Arcones, A Aryan, A Bandyopadhyay, A Banu, D W Bardayan, J Barnes, A Bauswein, T C Beers, J Bishop, T Boztepe, B Côté, M E Caplan, A E Champagne, J A Clark, M Couder, A Couture, S E de Mink, S Debnath, R J deBoer, J den Hartogh, P Denissenkov, V Dexheimer, I Dillmann, J E Escher, M A Famiano, R Farmer, R Fisher, C Fröhlich, A Frebel, C Fryer, G Fuller, A K Ganguly, S Ghosh, B K Gibson, T Gorda, K N Gourgouliatos, V Graber, M Gupta, W C Haxton, A Heger, W R Hix, W C G Ho, E M Holmbeck, A A Hood, S Huth, G Imbriani, R G Izzard, R Jain, H Jayatissa, Z Johnston, T Kajino, A Kankainen, G G Kiss, A Kwiatkowski, M La Cognata, A M Laird, L Lamia, P Landry, E Laplace, K D Launey, D Leahy, G Leckenby, A Lennarz, B Longfellow, A E Lovell, W G Lynch, S M Lyons, K Maeda, E Masha, C Matei, J Merc, B Messer, F Montes, A Mukherjee, M R Mumpower, D Neto, B Nevins, W G Newton, L Q Nguyen, K Nishikawa, N Nishimura, F M Nunes, E O’Connor, B W O’Shea, W-J Ong, S D Pain, M A Pajkos, M Pignatari, R G Pizzone, V M Placco, T Plewa, B Pritychenko, A Psaltis, D Puentes, Y-Z Qian, D Radice, D Rapagnani, B M Rebeiro, R Reifarth, A L Richard, N Rijal, I U Roederer, J S Rojo, J S K, Y Saito, A Schwenk, M L Sergi, R S Sidhu, A Simon, T Sivarani, Á Skúladóttir, M S Smith, A Spiridon, T M Sprouse, S Starrfield, A W Steiner, F Strieder, I Sultana, R Surman, T Szücs, A Tawfik, F Thielemann, L Trache, R Trappitsch, M B Tsang, A Tumino, S Upadhyayula, J O Valle Martínez, M Van der Swaelmen, C Viscasillas Vázquez, A Watts, B Wehmeyer, M Wiescher, C Wrede, J Yoon, R G T Zegers, M A Zermane, M Zingale

Date Published: 15th Nov 2022

Publication Type: Journal

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