Geometry & microstructure

Introduction

The computational-geometry/microstructure-modeling-based part of the proposal has the following aims:

First, we would like to contribute to efforts on standardizing a controlled vocabulary, definitions for these terms, and relations between the terms, for computational-geometry-based descriptions of the microstructure of materials and atomic configurations used when characterizing materials in experiments and computer simulations.

As far as NeXus is concerned, the here proposed distinct sets of simple geometric primitives and shapes offer a complementary alternative to the already existent base classes in NeXus for constructive solid geometry such as NXcsg, NXoff_geometry, or NXquadric to name but a few.

Second, we would like to explore with this proposal how we can harmonize terms frequently used by materials scientists in the field of condensed-matter physics with definitions and terms offer by the NOMAD MetaInfo description.

Third, the proposal should yield a substantiated set of arguments and suggestions how descriptors for the structure and atomic architecture of materials can be harmonized. With this we especially would like to reach out and intensify the cooperation between the materials-science-related consortia of the German National Research Infrastructure, specifically, FAIRmat, NFDI-MatWerk, NFDI4Ing, NFDI4Chem, NFDI4Cat, MaRDi, and DAPHNE.

Physics background

Microstructural features or crystal defects are spatial arrangements of atoms. Given their specific atomic arrangement and composition, such features have specific constraints on the degrees of freedom how atoms can arrange. This causes that these defects have specific properties. Provided well-defined coarse-graining procedures are used and regions-of-interest and/or regions-of-applicability are defined, microstructural features are often characterized and modelled to have associated thermodynamic descriptors.

Another motivation for the proposal was the observation that frequently the design of file formats for simulation software in the computational materials science especially those tools at the interface between condensed-matter physics and materials engineering are frequently reimplementing the wheel (at least partly) when it comes to decide how to store e.g. atom and feature positions or shape of regions-of-interest, grids, crystals, grains, precipitates, and dislocations.

Maybe this is a historical burden given the large set of technical terms and jargon in place, which then motivated pragmatic solutions that resulted in many research groups have developed similar formats using similar descriptions.

We see this work on base classes and application definitions not primarily an effort to improve and extend NeXus for now. Rather this part of the proposal is an effort to support activities in materials science to work towards common terminology and using controlled vocabularies more frequently. These are the foundation for more sophisticated thoughts about practically useful ontologies.

Defining crystal defects is a question of how to coarse-grain a given spatio- temporal set of atoms, each having a nuclid type and position/trajectory. In most cases, such a coarse-graining is an ill-posed task because different mathematical/geometrical methods exists how a point, a line, a surface, or a volumetric defect can be described and be spatio-temporally constrained through a geometrical model with defined geometric primitives and associated coarser-scale properties.

The key motivation to such coarse-graining is to reduce the complexity of the description. On the one hand to support visualization and scientific analyses - not only of crystal defect arrangements. On the other hand it is the hope that using descriptors at a coarser level, i.e. nanometer, micrometer, and larger, it is still possible to find sufficiently accurate and precise descriptors which avoid that one has to account for the dynamics of each atom to predict or understand the properties of defects and their dynamics.

Nevertheless, experience has shown that computational-geometry-based descriptions when combined with hierarchical clustering/labeling methods, applied on set of atoms and features turn out to yield useful descriptors. Examples include point, line, surface defects, such as vacancies, solute cluster, dislocations, disconnections, interfaces to name but a few.

Base Classes

We propose the following base classes, starting with a set of descriptors for frequently used shapes and geometric primitives:

NXcg_sphere_set:

A description for a set of possibly dissimilar spheres.

NXcg_ellipsoid_set:

A description for a set of possibly dissimilar rotated ellipsoids.

NXcg_cylinder_set:

A description for a set of possibly dissimilar rotated cylinders.

NXcg_point_set:

A collection of points with labels or mark data.

NXcg_polyline_set:

A collection of lines and linearized segments.

NXcg_triangle_set:

A collection (or soup) of triangles.

NXcg_parallelogram_set:

A collection of possibly dissimilar parallelograms.

NXcg_triangulated_surface_mesh:

A mesh of triangles.

NXcg_polygon_set:

A collection (or soup) of polygons.

NXcg_polyhedron_set:

A collection (or soup) of polyhedra.

NXcg_roi_set:

A container to host a number of different types of primitives.

NXcg_tetrahedron_set:

A collection (or soup) of tetrahedra.

NXcg_hexahedron_set:

A collection (or soup) of hexahedra with capabilities to represent also simpler (bounding) boxes for e.g. binary trees.

These base classes make use of new base classes which describe data structures:

NXcg_face_list_data_structure:

In essence, the usual way how polygon/polyhedra data are reported: Via a list of vertices and faces with identifier and properties.

NXcg_half_edge_data_structure:

A half-edge data structure is a useful complementary descriptor for polygon/polyhedra which enables topological analyses and traversal of the graph how polygons and polyhedra can alternatively be described.

NXcg_unit_normal_set:

As an additional structuring element especially for meshes, well-documented normal information is crucial for distance computations.

NXcg_geodesic_mesh:

Geodesic meshes are useful for all applications when meshing the surface of a sphere.

NXcg_alpha_complex:

Alpha shapes and alpha wrappings, specifically the special case of the convex hull, are frequently used geometrical models for describing a boundary or edge to a set of geometric primitives.

Furthermore, we propose a few base classes for operations when working with discretized representations of material (area or volume) which can be useful not only for stencil-based methods:

NXcg_grid:

A grid of cells.

NXisocontour:

A description for isocontour descriptions.

NXcg_marching_cubes:

An approach to store metadata of a specific implementation of the Marching Cubes algorithm, whose sensitivity to specific topological configurations is known to result in different triangle soups.

NXdelocalization:

An approach to document procedures whereby a scalar field is smoothened in a controlled manner.

Assuming that these base classes can serve as building blocks, we would like to test with the proposal also how these base classes can be applied in base classes for specific types of microstructural features and/or utility classes to hold metadata for these features:

NXsimilarity_grouping:

An alias for NXclustering.

NXclustering:

A description for clustering of objects (such as atoms or features).

NXorientation_set:

A set of rotations to describe the relative orientation of members of a set of features/objects.

NXslip_system_set:

Metadata to a set of slip system/slip system family for a given crystal structure.

NXms_atom_set:

Metadata to a set of atoms.

NXms_dislocation_set:

Metadata of a set of dislocation/disconnection (line) defects.

NXms_interface_set:

Metadata to a set of interfaces between crystals.

NXms_crystal_set:

A set of crystals, for e.g. a polycrystal, phases, grains, precipitates.

NXms_snapshot:

A container to describe the state of microstructural features at a given point in time.

NXms_snapshot_set:

The corresponding class to hold a set of NXms_snapshot objects.

NXchemical_composition:

(Chemical) composition of a sample or a set of things.

Furthermore, we found that it can be useful to have a set of base classes with which software documents it state and gives a summary for users about the performance and elapsed time measured while processing data. These utility classes include:

NXprogram:

A named and version of a program of library/component of a larger software framework.

NXcs_filter_boolean_mask:

A boolean mask.

NXcs_prng:

Metadata of a pseudo-random number generator (PRNG) algorithm.

NXcs_profiling:

A structuring group holding a set of NXcs_profiling_event instances.

NXcs_profiling_event:

Profiling/benchmark data to an event of tracking an algorithm/computational step.

NXcs_computer:

Metadata of a computer.

NXcs_cpu:

Metadata of a central processing unit.

NXcs_gpu:

Metadata of a graphical processing unit / accelerator.

NXcs_mm_sys:

Metadata of the (main) memory (sub-)system.

NXcs_io_sys:

Metadata of the input/output system.

NXcs_io_obj:

Metadata of a component storing data of an NXcs_io_sys instance.

Application definitions for ICME models

To bridge to our colleagues from the NFDI-MatWerk and NFDI4Ing consortia we have created an example how the proposed components of the nexus-fairmat-proposal can be used to create data schemes for vanilla-type ICME microstructure models. ICME is an abbreviation for Integrated Computational Materials Engineering, which is a design strategy and workflow whereby physics-based modelling of microstructure evolution at the mesoscopic scale is used to understand the relations between the microstructure and technological relevant descriptors for the properties of materials.

To begin with we propose the following draft application definitions.

NXms:

An application definition for arbitrary spatiotemporally resolved simulations.

NXms_score_config:

A specific example how NXapm_paraprobe_config_ranger can be specialized for documenting the configuration of a computer simulation with the static recrystallization cellular automata model SCORE.

NXms_score_results:

A specific example how NXms can be specialized for documenting results of computer simulations with the static recrystallization cellular automata model SCORE.