BiGmax Workshop 2021

Contribution List

54. Computational material synthesis: Atomistic and molecular dynamics, and bio-inspired AI (30 min talk + 15 min discussion)

Markus Buehler (invited) (MIT)

14/04/2021, 13:45

Talk

Session I

Nature produces a variety of materials with many functions, often out of simple and abundant materials, and at low energy. Such systems - examples of which include silk, bone, nacre or diatoms - provide broad inspiration for engineering. Here we explore the translation of biological composites to engineering applications, using a variety of tools including molecular modeling, AI and machine...

39. AI-driven discovery of material "genes": application to CO2 activation on semiconductor oxide surfaces (12 min talk + 3 min discussion)

Luca Ghiringhelli (Fritz Haber Institute of the Max Planck Society)

14/04/2021, 14:30

Talk

Session I

Using subgroup discovery (SGD), an AI approach that discovers statistically exceptional subgroups in a dataset, we develop a strategy for a rational design of catalytic materials. SGD allows for the identification of distinct, possibly competing mechanisms of a catalytic activation. Here, it is applied to the problem of converting CO$_2$ into useful chemicals. We demonstrate that the bending...

50. Design of high-entropy Invar alloys via machine learning (12 min talk + 3 min discussion)

Ziyuan Rao (max-planck-institut für eisenforschung gmbh)

14/04/2021, 14:45

Talk

Session I

Invar alloys exhibit a very low thermal expansion coefficient (TEC) below 2×10−6 K−1 around room temperature. There is a strong impetus to design novel Invar alloys with better physical, mechanical and chemical properties. Here, we develop and apply an active learning strategy to accelerate the design of novel Invar alloys in a practically infinite compositional space of quaternary and quinary...

43. Data-driven search for drug–membrane permeability models (12 min talk + 3 min discussion)

Arghya Dutta (Max Planck Institute for Polymer Research)

14/04/2021, 15:00

Talk

Session I

Passive drug–membrane permeability of a drug molecule quantifies its capacity to cross cell membranes on the
way of reaching its target. In this contribution, I will present results from our work where we used sure-independence screening and sparsifying operator (SISSO) to find equations for the permeability coefficient that combine both hydrophobicity and acidity of the drugs. The predicted...

51. Data driven approaches to design damage tolerant Dual-phase steel microstructures (12 min talk + 3 min discussion)

Navyanth Kusampudi

14/04/2021, 15:15

Talk

Session I

Identifying representations and characterizing the microstructure features is crucial for developing the damage-tolerant dual-phase steels. These representations serve as variables to establish a structure-property relationship and to design microstructures of desired mechanical property. However, the complex nature of the DP steel microstructure, poses a challenge and the existing...

57. Model-Free Data-Driven Science: Cutting out the Middleman (30 min talk + 15 min discussion)

Michael Ortiz (invited) (Caltech/Universität Bonn)

14/04/2021, 16:15

Talk

Session II

42. Using phase-field models to coarse-grain data sets from scanning transmission electron microscopy (12 min talk + 3 min discussion)

Christoph Freysoldt (MPI Eisenforschung)

14/04/2021, 17:00

Talk

Session II

To extract transferable insights from scanning transmission electron microscopy (STEM), one must deal with noise arising from electron scattering and of the investigated sample. This noise hinders a quantitative analysis of the observation, notably when the features of interest lie in the gradients of the raw data. Physics-informed neural networks have been proposed as a means to incorporate...

46. High-performance data-anayltics and AI at MPCDF (12 min talk + 3 min discussion)

Andreas Marek (MPCDF)

14/04/2021, 17:15

Talk

Session II

Since few years, in addition to classical (simulation-based) HPC usage, we observe a steadily growing need of our users for support of high-performance data-analytics (HPDA) and AI workflows.
In this presentation, we will give an overview of the HPC clusters available at MPCDF for HPDA and AI workflows, the available (HPC-optimized) software stack and we will present recently introduced...

48. Uncovering the Relationship Between Thermal Conductivity and Anharmonicity with Symbolic Regression (12 min talk + 3 min discussion)

Thomas Purcell (Fritz Haber Institute)

14/04/2021, 17:30

Talk

Session II

Quantitatively understanding the link between anharmonicity and thermal conductivity, $\kappa$, is pivotal to the search for better thermal insulators. To help find this link we present new descriptors of $\kappa$ based on our new measure of anharmonicity, $\sigma^\mathrm{A}$. Using an updated sure-independence screening and sparsifying operator (SISSO) method, we find analytical expressions...

3. Resampling Base Distributions of Normalizing Flows (12 min talk + 3 min discussion)

Vincent Stimper (Max Planck Institute for Intelligent Systems)

14/04/2021, 17:45

Talk

Session II

Normalizing flows are a popular class of models for approximating probability distributions. However, in many tasks such as image generation benchmarks they are still outperformed by autoregressive models and generative adversarial networks. This is in part due to their invertible nature limiting their ability to model target distributions with a complex topological structure. Several...

55. 3D image analysis (30 min talk + 15 min discussion)

Dagmar Kainmueller (invited) (MDC Berlin)

15/04/2021, 09:30

Talk

Session III

Microscopy data is often large and 3d, and thus convolutional neural networks (CNNs) need to be applied in a tile-and-stitch manner to cope with GPU memory constraints. Concerning pixel-wise predictions obtained with UNet-style CNNs via tile-and-stitch, issues with discontinuities at output tile boundaries have been reported. However, a formal analysis of the causes has been lacking. In...

53. Towards an automatized data analysis of large 3d volumetric data (12 min talk + 3 min discussion)

Luca Curcuraci (Max-Planck-Institut für Kolloid- und Grenzflächenforschung), Markus Kühbach (Fritz Haber Institute, NOMAD Laboratory), Luca Bertinetti (Max Planck Institute of Colloids and Interfaces)

15/04/2021, 10:15

Talk

Session III

Recent developments in bio-imaging technologies have allowed researchers to collect larger and larger tomographic datasets which contain an immense amount of details. To achieve a quantitative understanding, however, these datasets need to be cleaned-up and segmented. These two tasks are tedious, very time consuming, and still performed mostly manually. In our work we aim to develop a full...

52. Convolutional neural network-assisted recognition of nanoscale L12 ordered structures in face-centred cubic alloys (12 min talk + 3 min discussion)

Yue Li (Max-Planck-Institut für Eisenforschung GmbH)

15/04/2021, 10:30

Talk

Session III

L12-type nano-ordered structures are typically fully-coherent with FCC matrix, which is challengeable to be characterized. Spatial distribution maps are used to probe local order within reconstructed APT data. However, it is almost impossible to manually analyse the complete point cloud in search for the partial crystallographic information retained within the data. Here, we proposed an...

40. Artificial-Intelligence-Driven Characterization of Crystallographic Interfaces from Electron Microscopy (12 min talk + 3 min discussion)

Byung Chul Yeo (Pukyong National University)

15/04/2021, 10:45

Talk

Session III

Characterizing crystallographic interfaces in synthetic nanomaterials is an important step for the design of novel materials. Trained materials scientists can assign interface structures of materials by looking at high-resolution imaging and diffraction data obtained by aberration-corrected scanning transmission electron microscopy (STEM). However, STEM datasets cannot be fully exploited due...

49. Machine-learning-enhanced time-of-flight mass spectrometry analysis (12 min talk + 3 min discussion)

Ye Wei (Max Planck institute for iron research)

15/04/2021, 11:45

Talk

Session III

Mass spectrometry is a widespread approach used to work out what the constituents of a material are. Atoms and molecules are removed from the material and collected, and subsequently, a critical step is to infer their correct identities based on patterns formed in their mass-to-charge ratios and relative isotopic abundances. However, this identification step still mainly relies on individual...

41. Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning (12 min talk + 3 min discussion)

Andreas Leitherer (Fritz Haber Institute of the Max Planck Society)

15/04/2021, 12:00

Talk

Session III

Due to their ability to recognize complex patterns, neural networks can drive a paradigm shift in the analysis of materials-science data. As a major improvement, we introduce a crystal-structure identification method based on Bayesian deep learning that is robust to structural noise and can treat more than 100 crystal structures. While being trained on ideal structures only, our method...

47. Learning Dynamics of STEM by Enforcing Physical Consistency with Phase-Field Models

Pawan Goyal (Max Planck Institute for Dynamics of Complex Technical Systems)

15/04/2021, 12:15

Poster

Poster session (meet us in gather.town)

In this poster, we present our research goals of a recently BiGmax funded project towards learning dynamics of scanning transmission electron microscopy (STEM) by incorporating physical consistency with phase-field models. The primary idea of this project is to develop machine learning (ML)-based modeling of an interpretable coarse-grained dynamic model utilizing in situ STEM video sequences...

45. Consistent atom probe representation for machine learning and data mining

Alaukik Saxena (Max-Planck-Institut für Eisenforschung GmbH )

15/04/2021, 12:25

Poster

Poster session (meet us in gather.town)

To correlate mechanical properties of Al alloys with chemical segregation in Atom Probe Tomography (APT), we have developed two approaches. In the first, we collect composition statistics from APT datasets for 2x2x2 nm voxels. These voxel compositions are then clustered in compositional space using Gaussian mixture models to automatically identify key phases and their corresponding statistical...

44. Gigascale electron event processing for band structure mapping

R. Patrick Xian (Fritz Haber Institute of the Max Planck Society), Dr Laurenz Rettig (Fritz Haber Institute of the Max Planck Society), Dr Ralph Ernstorfer (Fritz Haber Institute of the Max Planck Society)

15/04/2021, 12:35

Poster

Poster session (meet us in gather.town)

Mapping of the electronic band structures of materials using momentum microscopy requires processing single-electron events of a few to hundreds of gigabytes. We construct a flexible computational workflow that allows user interaction with billion-count single-electron events in these band mapping experiments. We demonstrate its compatibility with large facility and tabletop experimental...

58. Knowledge-Based Approaches in Catalysis and Energy Modelling (30 min talk + 15 min discussion)

Karsten Reuter (invited) (FHI Berlin)

15/04/2021, 14:00

Talk

Session IV

Data sciences are now also entering theoretical catalysis and energy related research with full might. Automatized workflows and the training of machine learning approaches with first-principles data generate predictive-quality insight into elementary processes and process energetics at undreamed-of pace. Computational screening and data mining allows to explore these data bases for promising...

37. NOMAD – A FAIR Data Sharing Platform for Materials Science (12 min talk + 3 min discussion)

Markus Scheidgen (Humboldt Universität zu Berlin / Fritz Haber Institut der Max Planck Gesellschaft)

15/04/2021, 14:45

Talk

Session IV

As an integral part of the FAIR-DI/FAIRmat initiatives, NOMAD is extending it's scope. NOMAD evolves from a central repository for publishing electronic structure codes data into a federated data management network that covers all branches of materials science. Instead of just using NOMAD to publish final results, we want to show how on-site installations of NOMAD can help to manage your local...

56. On Software Tools Which Assist Electron Microscopists with Sharing Metadata and Numerical Results in Accordance with the FAIR Data Stewardship Principles (12 min talk + 3 min discussion)

Markus Kühbach

15/04/2021, 15:00

Talk

Session IV

Microscopy and spectroscopy experiments and the associated computational and theoretical analyses of data from such experiments are the resources of laboratory and data-processing workflows that yield numerical data and contextualization through metadata. The purpose of such experiments is ideally accurate and precise delivery of quantitative evidence in support of or against a formulated set...

38. Approaches to FAIR TEM data (12 min talk + 3 min discussion)

Niels Cautaerts (Max-Planck-Institut für Eisenforschung)

15/04/2021, 15:15

Talk

Session IV

Transmission electron microscopy data is rich in quantitative information about materials, information that could in theory be coupled to atomistic simulations, but extracting and harnessing that information is non-trivial. Machine learning approaches may facilitate this, but these are hampered by the limited availability and interoperability of the data. In this talk we present approaches,...