| 1. |
- Faber, Felix A., et al.
(author)
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Machine Learning Energies of 2 Million Elpasolite (AB2D6) Crystals
- 2016
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In: Physical Review Letters. - : American Physical Society. - 0031-9007 .- 1079-7114. ; 117:13
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Journal article (peer-reviewed)abstract
- Elpasolite is the predominant quaternary crystal structure (AlNaK2F6 prototype) reported in the Inorganic Crystal Structure Database. We develop a machine learning model to calculate density functional theory quality formation energies of all ∼2×106 pristine ABC2D6 elpasolite crystals that can be made up from main-group elements (up to bismuth). Our model’s accuracy can be improved systematically, reaching a mean absolute error of 0.1 eV/atom for a training set consisting of 10×103 crystals. Important bonding trends are revealed: fluoride is best suited to fit the coordination of the D site, which lowers the formation energy whereas the opposite is found for carbon. The bonding contribution of the elements A and B is very small on average. Low formation energies result from A and B being late elements from group II, C being a late (group I) element, and D being fluoride. Out of 2×106 crystals, 90 unique structures are predicted to be on the convex hull—among which is NFAl2Ca6, with a peculiar stoichiometry and a negative atomic oxidation state for Al.
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| 2. |
- Faber, Felix, et al.
(author)
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Crystal structure representations for machine learning models of formation energies
- 2015
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In: International Journal of Quantum Chemistry. - : Wiley. - 0020-7608 .- 1097-461X. ; 115:16, s. 1094-1101
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Journal article (peer-reviewed)abstract
- We introduce and evaluate a set of feature vector representations of crystal structures for machine learning (ML) models of formation energies of solids. ML models of atomization energies of organic molecules have been successful using a Coulomb matrix representation of the molecule. We consider three ways to generalize such representations to periodic systems: (i) a matrix where each element is related to the Ewald sum of the electrostatic interaction between two different atoms in the unit cell repeated over the lattice; (ii) an extended Coulomb-like matrix that takes into account a number of neighboring unit cells; and (iii) an ansatz that mimics the periodicity and the basic features of the elements in the Ewald sum matrix using a sine function of the crystal coordinates of the atoms. The representations are compared for a Laplacian kernel with Manhattan norm, trained to reproduce formation energies using a dataset of 3938 crystal structures obtained from the Materials Project. For training sets consisting of 3000 crystals, the generalization error in predicting formation energies of new structures corresponds to (i) 0.49, (ii) 0.64, and (iii) 0.37eV/atom for the respective representations.
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| 3. |
- Goodall, Rhys E. A., et al.
(author)
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Rapid discovery of stable materials by coordinate-free coarse graining
- 2022
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In: Science Advances. - : AMER ASSOC ADVANCEMENT SCIENCE. - 2375-2548. ; 8:30
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Journal article (peer-reviewed)abstract
- A fundamental challenge in materials science pertains to elucidating the relationship between stoichiometry, stability, structure, and property. Recent advances have shown that machine learning can be used to learn such relationships, allowing the stability and functional properties of materials to be accurately predicted. However, most of these approaches use atomic coordinates as input and are thus bottlenecked by crystal structure identification when investigating previously unidentified materials. Our approach solves this bottleneck by coarse-graining the infinite search space of atomic coordinates into a combinatorially enumerable search space. The key idea is to use Wyckoff representations, coordinate-free sets of symmetry-related positions in a crystal, as the input to a machine learning model. Our model demonstrates exceptionally high precision in finding unknown theoretically stable materials, identifying 1569 materials that lie below the known convex hull of previously calculated materials from just 5675 ab initio calculations. Our approach opens up fundamental advances in computational materials discovery.
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| 4. |
- Lill, Christina M., et al.
(author)
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Closing the case of APOE in multiple sclerosis : no association with disease risk in over 29 000 subjects
- 2012
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In: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 558-562
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Journal article (peer-reviewed)abstract
- Background Single nucleotide polymorphisms (SNPs) rs429358 (ε4) and rs7412 (ε2), both invoking changes in the amino-acid sequence of the apolipoprotein E (APOE) gene, have previously been tested for association with multiple sclerosis (MS) risk. However, none of these studies was sufficiently powered to detect modest effect sizes at acceptable type-I error rates. As both SNPs are only imperfectly captured on commonly used microarray genotyping platforms, their evaluation in the context of genome-wide association studies has been hindered until recently.Methods We genotyped 12 740 subjects hitherto not studied for their APOE status, imputed raw genotype data from 8739 subjects from five independent genome-wide association studies datasets using the most recent high-resolution reference panels, and extracted genotype data for 8265 subjects from previous candidate gene assessments.Results Despite sufficient power to detect associations at genome-wide significance thresholds across a range of ORs, our analyses did not support a role of rs429358 or rs7412 on MS susceptibility. This included meta-analyses of the combined data across 13 913 MS cases and 15 831 controls (OR=0.95, p=0.259, and OR 1.07, p=0.0569, for rs429358 and rs7412, respectively).Conclusion Given the large sample size of our analyses, it is unlikely that the two APOE missense SNPs studied here exert any relevant effects on MS susceptibility.
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| 5. |
- Meitzner, Rico, et al.
(author)
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Impact of P3HT materials properties and layer architecture on OPV device stability
- 2019
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In: Solar Energy Materials and Solar Cells. - : Elsevier BV. - 0927-0248. ; 202
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Journal article (peer-reviewed)abstract
- We report a cooperative study conducted between different laboratories to investigate organic solar cell degradation with respect to P3HT material properties and different solar cell architectures. Various batches of P3HT were collected from different suppliers reflecting commercial availability as well as properties variability. Among the materials properties explicitly considered were the molar mass, dispersity, regio-regularity, impurities by trace metals and intrinsic doping evaluated from radical concentrations. Each of the participating laboratories contributing test devices applied their own layer stack, i.e. their own device architecture and layout. This variation was appreciated as another parameter for evaluation. Even though a large amount of devices failed due to extrinsic degradation effects, indeed, some materials properties were found to be more important than others for obtaining long lifetimes and high stability of P3HT-based polymer solar cells.
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