Structure maps for A I 4 A II 6(BO4)6X2 apatite compounds via data mining

Classification of apatite structures via topological data analysis: a framework for a 'Materials Barcode' representation of structure maps

This paper introduces the use of topological data analysis (TDA) as an unsupervised machine learning tool to uncover classification criteria in complex inorganic crystal chemistries. Using the apatite chemistry as a template, we track through the use of persistent homology the topological connectivity of input crystal chemistry descriptors on defining similarity between different stoichiometries of apatites. It is shown that TDA automatically identifies a hierarchical classification scheme within apatites based on the commonality of the number of discrete coordination polyhedra that constitute the structural building units common among the compounds. This information is presented in the form of a visualization scheme of a barcode of homology classifications, where the persistence of similarity between compounds is tracked. Unlike traditional perspectives of structure maps, this new “Materials Barcode” schema serves as an automated exploratory machine learning tool that can uncover structural associations from crystal chemistry databases, as well as to achieve a more nuanced insight into what defines similarity among homologous compounds.

Structure and thermal expansion behavior of Ca4La6−xNdx(SiO4)4(PO4)2O2 apatite for nuclear waste immobilization

In this study, Ca₄La_6−xNd_x(SiO₄)₄(PO₄)₂O₂ (x = 0, 1, 2, 3, 4, 5, and 6) apatites were explored for nuclear waste immobilization, and Nd³⁺ ions were used as the surrogate of radionuclides (such as Am³⁺, Cm³⁺, and Pu³⁺).

Informatics-Based Approaches for Accelerated Discovery of Functional Materials

This chapter is aimed at readers interested in the topic of informatics-based approaches for accelerated materials discovery, but who are unfamiliar with the nuances of the underlying principles and various types of powerful mathematical tools that are involved in formulating structure–property relationships. In an attempt to simplify the workflow of materials informatics, we decompose the paradigm into several core subtasks: hypothesis generation, database construction, data pre-processing, mathematical modeling, model validation, and finally hypothesis testing. We discuss each task and provide illustrative case studies, which apply these methods to various functional ceramic materials.

Mapping Chemical Selection Pathways for Designing Multicomponent Alloys: an informatics framework for materials design

A data driven methodology is developed for tracking the collective influence of the multiple attributes of alloying elements on both thermodynamic and mechanical properties of metal alloys. Cobalt-based superalloys are used as a template to demonstrate the approach. By mapping the high dimensional nature of the systematics of elemental data embedded in the periodic table into the form of a network graph, one can guide targeted first principles calculations that identify the influence of specific elements on phase stability, crystal structure and elastic properties. This provides a fundamentally new means to rapidly identify new stable alloy chemistries with enhanced high temperature properties. The resulting visualization scheme exhibits the grouping and proximity of elements based on their impact on the properties of intermetallic alloys. Unlike the periodic table however, the distance between neighboring elements uncovers relationships in a complex high dimensional information space that would not have been easily seen otherwise. The predictions of the methodology are found to be consistent with reported experimental and theoretical studies. The informatics based methodology presented in this study can be generalized to a framework for data analysis and knowledge discovery that can be applied to many material systems and recreated for different design objectives.

Electronically driven structural transitions inA10(PO4)6F2apatites (A= Ca, Sr, Pb, Cd and Hg)

It is shown that there is a dynamic lattice instability in the aristotypeP63/mstructure ofA10(PO4)6F2apatites containing divalentA-site Cd or Hg cations with (n − 1)d10ns0electronic configurations. The distortion to a low-symmetry P\bar{1} triclinic structure is driven by an electronic mechanism rather than from ionic size mismatch. Our theoretical work provides key insights into the role of the electronic configurations ofAcations in fluorapatites.