Kohn–Sham density functional theory is widely used for screening color centers in semiconductors. While the Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation functional is efficient, its accuracy in describing defects is often not sufficient. The Heyd–Scuseria–Ernzerhof (HSE) functional is more accurate but computationally expensive, making it impractical for large-scale screening. This study evaluates the strongly constrained and appropriately normed (SCAN) family of meta-GGA functionals as potential alternatives to PBE for characterizing NV-like color centers in 4H-SiC using the Automatic Defect Analysis and Qualification (ADAQ) framework. We examine nitrogen, oxygen, fluorine, sulfur, and chlorine vacancies in 4H-SiC, focusing on applications in quantum technology. Our results show that SCAN and r2SCAN achieve a greater accuracy than PBE, approaching HSE's precision at a lower computational cost. This suggests that the SCAN family offers a practical improvement for screening new color centers, with computational demands similar to PBE.  

Units of measure are central in all areas of science and technology. There are several ontologicalframeworks aiming to improve interoperability and precision in digital data exchange of quantitiesinvolving units. We introduce an ontology that specifically targets challenges for handling units acrossdatabases of computational and experimental data from various sources. The ontology is created usingdefinition files from the community-driven OPTIMADE standard for a common API for materialsdatabases. The resulting ontology allows addressing data integration challenges encountered in thateffort, including (i) referencing both specific and more general instances of units that have changedover time; (ii) the use of unit systems to define short domain-relevant identifiers for a collection of unitsthat make sense within a specific subdomain, rather than having to adopt globally standardized namingschemes; (iii) specifications of relationships between units that enables tools to convert between them;and (iv) units not part of the International System of Units (SI) can be represented without defining themin SI units or using SI system conventions. This paper provides a brief survey of existing ontologiesfor units of measure and then presents the design and discuss features of an ontology based on theOPTIMADE unit definitions.

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development. The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a federation of databases, enhancing the accessibility and discoverability of materials and chemical data.

In a GraphQL Web API, a so-called GraphQL schema defines the types of data objects that can be queried, and so-called resolver functions are responsible for fetching the relevant data from underlying data sources. Thus, we can expect to use GraphQL not only for data access but also for data integration, if the GraphQL schema reflects the semantics of data from multiple data sources, and the resolver functions can obtain data from these data sources and structure the data according to the schema. However, there does not exist a semantics-aware approach to employ GraphQL for data integration. Furthermore, there are no formal methods for defining a GraphQL API based on an ontology.In this work, we introduce a framework for using GraphQL in which a global domain ontology informs the generation of a GraphQL server that answers requests by querying heterogeneous data sources.The core of this framework consists of an algorithm to generate a GraphQL schema based on an ontology and a generic resolver function based on semantic mappings. We provide a prototype, OBG-gen, of this framework, and we evaluate our approach over a real-world data integration scenario in the materials design domain and two synthetic benchmark scenarios (Linköping GraphQL Benchmark and GTFS-Madrid-Bench). The experimental results of our evaluation indicate that: (i) our approach is feasible to generate GraphQL servers for data access and integration over heterogeneous data sources, thus avoiding a manual construction of GraphQL servers, and (ii) our data access and integration approach is general and applicable to different domains where data is shared or queried via different ways.

Defects in semiconductors have in recent years been revealed to have interesting properties in the venture towards quantum technologies. In this regard, silicon carbide has shown great promise as a host for quantum defects. In particular, the ultrabright AB photoluminescence lines in 4⁢H-Si⁢C are observable at room temperature and have been proposed as a single-photon quantum emitter. These lines have previously been studied and assigned to the carbon–antisite-vacancy (CAV) pair. In this paper, we report on new measurements of the AB lines’ temperature dependence, and carry out an in-depth computational study on the optical properties of the CAV defect. We find that the CAV defect has the potential to exhibit several different zero-phonon luminescences with emissions in the near-infrared telecom band, in its neutral and positive charge states. However, our measurements show that the AB lines only consist of three nonthermally activated lines instead of the previously reported four lines; meanwhile, our calculations on the CAV defect are unable to find optical transitions in full agreement with the AB-line assignment. In light of our results, the identification of AB lines and the associated room-temperature emission require further study.

In the materials design domain, much of the data from materials calculations is stored in different heterogeneous databases with different data and access models. Therefore, accessing and integrating data from different sources is challenging. As ontology-based access and integration alleviates these issues, in this paper we address data access and interoperability for computational materials databases by developing the Materials Design Ontology. This ontology is inspired by and guided by the OPTIMADE effort that aims to make materials databases interoperable and includes many of the data providers in computational materials science. In this paper, first, we describe the development and the content of the Materials Design Ontology. Then, we use a topic model-based approach to propose additional candidate concepts for the ontology. Finally, we show the use of the Materials Design Ontology by a proof-of-concept implementation of a data access and integration system for materials databases based on the ontology.

Doping of a two-dimensional (2D) material by impurity atoms occurs via two distinct mechanisms: absorption of the dopants by the 2D crystal or adsorption on its surface. To distinguish the relevant mechanism, we systematically dope 53 experimentally synthesized 2D monolayers by 65 different chemical elements in both absorption and adsorption sites. The resulting 17,598 doped monolayer structures were generated using the newly developed ASE DefectBuilder—a Python tool to set up point defects in 2D and bulk materials—and subsequently relaxed by an automated high-throughput density functional theory (DFT) workflow. We find that interstitial positions are preferred for small dopants with partially filled valence electrons in host materials with large lattice parameters. In contrast, adatoms are favored for dopants with a low number of valence electrons due to lower coordination of adsorption sites compared to interstitials. The relaxed structures, characterization parameters, defect formation energies, and magnetic moments (spins) are available in an open database to help advance our understanding of defects in 2D materials.

A GraphQL server contains two building blocks: (1) a GraphQL schema defining the types of data objects that can be requested; (2) resolver functions fetching the relevant data from underlying data sources. GraphQL can be used for data integration if the GraphQL schema provides an integrated view of data from multiple data sources, and the resolver functions are implemented accordingly.However, there does not exist a semantics-aware approach to use GraphQL for data integration.We proposed a framework using GraphQL for data integration in which a global domain ontology informs the generation of a GraphQL server. Furthermore, we implemented a prototype of this framework, OBG-gen. In this paper, we demonstrate OBG-gen in a real-world data integration scenario in the materials design domain and in  a synthetic benchmark scenario.

Due to importance of data FAIRness (Findable, Accessible, Interoperable, Reusable), ontologies as a means to make data FAIR have attracted more and more attention in different communities and are being used in semantically-enabled applications. However, to obtain good results while using ontologies in these applications, high quality ontologies are needed of which completeness is one of the important aspects. An ontology lacking information can lead to missing results. In this paper we present a tool, Phrase2Onto, that supports users in extending ontologies to make the ontologies more complete. It is particularly suited for ontology extension using a phrase-based topic model approach, but the tool can support any extension approach where a user needs to make decisions regarding the appropriateness of using phrases to define new concepts. We describe the functionality of the tool and a user study using Pizza Ontology. The user study showed  a good usability of the system and high task completion. Further, we report on a real application where we extend the Materials Design Ontology.

The negatively charged silicon vacancy (V-Si(-)) in silicon carbide is a well-studied point defect for quantum applications. At the same time, a closer inspection of ensemble photoluminescence and electron paramagnetic resonance measurements reveals an abundance of related but so far unidentified signals. In this study, we search for defects in 4H-SiC that explain the above magneto-optical signals in a defect database generated by automatic defect analysis and qualification (ADAQ) workflows. This search reveals only one class of atomic structures that exhibit silicon-vacancy-like properties in the data: a carbon anti-site (C-Si) within sub-nanometer distances from the silicon vacancy only slightly alters the latter without affecting the charge or spin state. Such a perturbation is energetically bound. We consider the formation of V-Si(-) + C-Si; up to 2 nm distance and report their zero phonon lines and zero field splitting values. In addition, we perform high-resolution photoluminescence experiments in the silicon vacancy region and find an abundance of lines. Comparing our computational and experimental results, several configurations show great agreement. Our work demonstrates the effectiveness of a database with high-throughput results in the search for defects in quantum applications.