arXiv subjects

Rickard Armiento

Publications and source records attributed to Rickard Armiento.

At least 19 recordsLinked to original sources

arXiv2026

Color Centers in Cubic Boron Nitride

Cubic boron nitride (c-BN) is a wide-bandgap semiconductor (WBGS) with potential applications in both power electronics and quantum technologies. Color centers in WBGS can be used as single photon emitters and quantum sensors. Several zero phonon lines have been measured in c-BN experiment but not yet identified. To systematically probe the combinatorially complex chemical space of defects, we generate a large-scale point defect data set for c-BN. We apply density functional theory calculation implemented in a high-throughput workflow Automatic Defect Analysis and Qualification (ADAQ) to broadly screen for point defect complexes containing s- or p-elements. More than 8000 defects have been calculated in different charge and spin states. The calculated properties are stored in defect database and are then filtered to find defects with properties similar to the NV-center in diamond. More accurate calculations using hybrid functionals are then performed on a selected set of promising defects to further assess their suitability for quantum technology. In particular, we reexamined the ONVB defect which likely explains the GC-2 line. The hybrid calculations also suggest other defect candidates with bright emission, such as two carbon defects and the NaB- defect.

cond-mat.mtrl-sci↗

arXiv2026

Symmetry-restricted energy landscapes as a benchmark for machine learned interatomic potentials

Machine learned interatomic potentials (MLIPs) are becoming a standard method for DFT-level accurate molecular dynamics simulation and large-scale studies of crystal energetics. Increasingly popular are universal pre-trained potentials, also called foundation models, based one, e.g. the MACE, CHGNet, M3GNet, ORB, and SevenNet architectures. While there are many benchmarks of these models using validation errors and materials discovery tasks, their fidelity in reproducing the detailed features of potential energy surfaces (PES) is not understood to the same degree. We evaluate the accuracy of these potentials by systematically probing their predicted energy landscapes. Two-dimensional slices of the potential energy surface are constructed where the atomic positions are varied along selected Wyckoff degrees of freedom within a fixed crystal symmetry. This approach enables a direct, visual comparison of the interatomic potentials and DFT-calculated surfaces which reveals potential artifacts e.g., arising from unique local environments. Our analysis highlights the strengths and limitations of different potentials in capturing local minima, saddle points, and overall PES topology, offering insights into the physical accuracy of current pre-trained IAPs and providing benchmarks for future model development.

cond-mat.mtrl-sci↗

arXiv2026

Screening 39 billion protostructures for materials discovery

Large-scale computational surveys are increasingly used to map the landscape of stable crystalline materials. We report a high-throughput energy screening of inorganic crystals that enumerates binary and ternary compositions up to a specified unit-cell complexity, yielding 39 billion protostructures. Candidates predicted to lie on or near the convex hull are retained, and their degrees of freedom are explored via Latin hypercube sampling followed by relaxation with machine-learned interatomic potentials. The resulting dataset contains 81 million locally relaxed crystal structures spanning 4495 ternary phase diagrams constructed from elements ranging from lithium to bromine and contains 88,498 crystal prototypes not present in existing crystal-structure databases. The methods are validated both for three well-explored materials systems, Zr-Zn-N, Ti-Zn-N, and Hf-Zn-N, and by comparing with known data for structures resulting from the larger screening. The work provides a systematic map of low-energy compositional-structural space and a large, structured pool of candidates for downstream property evaluation and materials design.

cond-mat.mtrl-sci↗

arXiv2025

High-Throughput Quantification of Altermagnetic Band Splitting

Altermagnetism represents a recently established class of collinear magnetism that combines zero net magnetization with momentum-dependent spin polarization, enabled by symmetry constraints rather than spin-orbit coupling. This distinctive behavior gives rise to sizable spin splitting even in materials composed of light, earth-abundant elements, offering promising prospects for next-generation spintronics applications. Despite growing theoretical and experimental interest, the discovery of altermagnetic materials remains limited due to the complexity of magnetic symmetry and the inefficiency of conventional approaches. Here, we present a comprehensive high-throughput screening of the entire MAGNDATA database, integrating symmetry analysis with spin-polarized density functional theory (DFT) calculations to identify and characterize altermagnetic candidates. Our workflow uncovers 173 materials exhibiting significant spin splitting ($\geq 50$ meV within $\pm 3$ eV of the Fermi level), spanning both metallic and semiconducting systems. Crucially, our momentum-resolved analysis reveals that the spin splitting varies strongly across the Brillouin zone, and that the maximal splitting tends to occur away from the high-symmetry paths, a result that directly informs and guides future photoemission experiments. By expanding the catalog of known altermagnets and elucidating the symmetry-protected origins of spin splitting, this work lays a robust foundation for future experimental and theoretical advances in spintronics and quantum materials discovery.

cond-mat.mtrl-sci↗

arXiv2025

High-Throughput Exploration of NV-like Color Centers Across Host Materials

Point defects in semiconductors offer a promising platform for advancing quantum technologies due to their localized energy states and controllable spin properties. Prior research has focused on a limited set of defects within materials such as diamond, silicon carbide, and hexagonal boron nitride. We present a high-throughput study to systematically identify and evaluate point defects across a diverse range of host materials, aiming to uncover previously unexplored defects in novel host materials suitable for use in quantum applications. A range of host materials are selected for their desirable properties, such as appropriate bandgaps, crystal structure, and absence of d- or f-electrons. The Automatic Defect Analysis and Qualification (ADAQ) software framework is used to generate vacancies, substitutions with s- and p-elements, and interstitials in these materials and use density functional theory to calculate key properties such as Zero-Phonon Lines (ZPLs), ionic displacements, Transition Dipole Moments (TDMs), and formation energies. Special attention is given to charge correction methods for materials with dielectric anisotropy. We uncover new defect-host combinations with advantageous properties for quantum applications: 28 defects across 11 isotropic and 2 anisotropic host materials show properties similar to the nitrogen-vacancy (NV) center in diamond. Beryllium (Be) substitutional defects in SrS, MgS, and SrO emerge as particularly promising. These findings contribute to diversifying and enhancing the materials available for quantum technologies.

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arXiv2025

WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry

Crystalline materials often exhibit a high level of symmetry. However, most generative models do not account for symmetry, but rather model each atom without any constraints on its position or element. We propose a generative model, Wyckoff Diffusion (WyckoffDiff), which generates symmetry-based descriptions of crystals. This is enabled by considering a crystal structure representation that encodes all symmetry, and we design a novel neural network architecture which enables using this representation inside a discrete generative model framework. In addition to respecting symmetry by construction, the discrete nature of our model enables fast generation. We additionally present a new metric, Fr\'echet Wrenformer Distance, which captures the symmetry aspects of the materials generated, and we benchmark WyckoffDiff against recently proposed generative models for crystal generation. As a proof-of-concept study, we use WyckoffDiff to find new materials below the convex hull of thermodynamical stability.

cond-mat.mtrl-sci↗

arXiv2025

Theoretical characterization of NV-like defects in 4H-SiC using ADAQ with the SCAN and r2SCAN meta-GGA functionals

Kohn-Sham density functional theory (DFT) is widely used for screening color centers in semiconductors. While the Perdew-Burke-Ernzerhof (PBE) functional is efficient, it often lacks precision in describing defects. The Heyd-Scuseria-Ernzerhof (HSE) functional is more accurate but computationally expensive, making it impractical for large-scale screening. However, third-rung functionals of "Jacob's ladder" remain largely under explored in this context. 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 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.

cond-mat.mtrl-sci↗

arXiv2024

Predicting the Curie temperature in substitutionally disordered alloys using a first-principles based model

When exploring new magnetic materials, the effect of alloying plays a crucial role for numerous properties. By altering the alloy composition, it is possible to tailor, e.g., the Curie temperature ($T_\text{C}$). In this work, $T_\text{C}$ of various alloys is investigated using a previously developed technique [Br\"{a}nnvall et al. Phys. Rev. Mat. (2024)] designed for robust predictions of $T_\text{C}$ across diverse chemistries and structures. The technique is based on density functional theory calculations and utilizes the energy difference between the magnetic ground state and the magnetically disordered paramagnetic state. It also accounts for the magnetic entropy in the paramagnetic state and the number of nearest magnetic neighbors. The experimentally known systems, Fe$_{1-x}$Co$_x$, Fe$_{1-x}$Cr$_x$, Fe$_{1-x}$V$_x$, NiMnSb-based Heusler alloys, Ti$_{1-x}$Cr$_x$N, and Co$_{1-x}$Al$_x$ are investigated. The experimentally unexplored system Fe$_{1-x}$Tc$_x$ is also tested to demonstrate the usefulness of the developed method in guiding future experimental efforts. This work demonstrates the broad applicability of the developed method across various systems, requiring less hands-on adjustments compared to other theoretical approaches.

cond-mat.mtrl-sci↗

arXiv2024

Temperature dependence of the AB-lines and Optical Properties of the Carbon-Antisite Vacancy Pair in 4H-SiC

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 ultra-bright AB photoluminescence lines in 4H-SiC are observable at room temperature and have been proposed as a single-photon quantum emitter. These lines have been previously studied and assigned to the carbon antisite-vacancy pair (CAV). 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 non-thermally 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 the light of our results, the identification of the AB-lines and the associated room temperature emission require further study.

cond-mat.mtrl-sci↗

arXiv2024

Evaluating and improving the predictive accuracy of mixing enthalpies and volumes in disordered alloys from universal pre-trained machine learning potentials

The advent of machine learning in materials science opens the way for exciting and ambitious simulations of large systems and long time scales with the accuracy of ab-initio calculations. Recently, several pre-trained universal machine learned interatomic potentials (UPMLIPs) have been published, i.e., potentials distributed with a single set of weights trained to target systems across a very wide range of chemistries and atomic arrangements. These potentials raise the hope of reducing the computational cost and methodological complexity of performing simulations compared to models that require for-purpose training. However, the application of these models needs critical evaluation to assess their usability across material types and properties. In this work, we investigate the application of the following UPMLIPs: MACE, CHGNET, and M3GNET to the context of alloy theory. We calculate the mixing enthalpies and volumes of 21 binary alloy systems and compare the results with DFT calculations to assess the performance of these potentials over different properties and types of materials. We find that small relative energies necessary to correctly predict mixing energies are generally not reproduced by these methods with sufficient accuracy to describe correct mixing behaviors. However, the performance can be significantly improved by supplementing the training data with relevant training data. The potentials can also be used to partially accelerate these calculations by replacing the ab-initio structural relaxation step.

cond-mat.mtrl-sci↗

arXiv2024

Predicting the Curie temperature of magnetic materials with automated calculations across chemistries and structures

We develop a technique for predicting the Curie temperature of magnetic materials using density functional theory calculations suitable to include in high-throughput frameworks. We apply four different models, including physically relevant observables and assess numerical constants by studying 32 ferro- and ferrimagnets. With the best-performing model, the Curie temperature can be predicted with a mean absolute error of approximately 126 K. As predictive factors, the models consider either the energy differences between the magnetic ground state and a magnetically disordered paramagnetic state, or the average constraining fields acting on magnetic moments in a disordered local moments calculation. Additionally, the energy differences are refined by incorporating the magnetic entropy of the paramagnetic state and the number of nearest magnetic neighbors of the magnetic atoms. The most advanced model is found to extend well into Fe$_{1-x}$Co$_x$ alloys, indicating the potential efficacy of utilizing our model in designing materials with tailored Curie temperatures by altering alloy compositions. This examination can illuminate the factors influencing magnetic transition temperatures in magnetic materials and provide insights into how they can be employed to make quantitative predictions of Curie temperatures. Our approach is not restricted to specific crystal structures or chemical compositions. It offers a more cost-effective alternative, in terms of human time and need for hands-on oversight, to other density functional theory methods for predicting the Curie temperature. As a result, it provides a practical strategy for conducting high-throughput screening for new technologically applicable magnetic materials. Alternatively, it can complement ML-based screening of magnetic materials by integrating physical principles into such approaches, thereby enhancing their prediction accuracy.

cond-mat.mtrl-sci↗

arXiv2024

Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

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 upcoming 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.

cond-mat.mtrl-sci↗

arXiv2023

Identifying Crystal Structures Beyond Known Prototypes from X-ray Powder Diffraction Spectra

The large amount of powder diffraction data for which the corresponding crystal structures have not yet been identified suggests the existence of numerous undiscovered, physically relevant crystal structure prototypes. In this paper, we present a scheme to resolve powder diffraction data into crystal structures with precise atomic coordinates by screening the space of all possible atomic arrangements, i.e., structural prototypes, including those not previously observed, using a pre-trained machine learning (ML) model. This involves (i) enumerating all possible symmetry-confined ways in which a given composition can be accommodated in a given spacegroup, (ii) ranking the element-assigned prototype representations using energies predicted using the Wren ML model [Sci.Adv.8, eabn4117 (2022)], (iii) assigning and perturbing atoms along the degree of freedom allowed by the Wyckoff positions to match the experimental diffraction data (iv) validating the thermodynamic stability of the material using density-functional theory (DFT). An advantage of the presented method is that it does not rely on a database of previously observed prototypes and is, therefore capable of finding crystal structures with entirely new symmetric arrangements of atoms. We demonstrate the workflow on unidentified XRD spectra from the ICDD database and identify a number of stable structures, where a majority turns out to be derivable from known prototypes. However, at least two are found not to be part of our prior structural data sets.

cond-mat.mtrl-sci↗

arXiv2023

ADAQ-SYM: Automated Symmetry Analysis of Defect Orbitals

Quantum technologies like single photon emitters and qubits can be enabled by point defects in semiconductors, with the NV-center in diamond being the most prominent example. There are many different semiconductors, each potentially hosting interesting defects. The symmetry properties of the point defect orbitals can yield useful information about the behavior of the system, such as the interaction with polarized light. We have developed a tool to perform symmetry analysis of point defect orbitals obtained by plane-wave density functional theory simulations. The software tool, named ADAQ-SYM, calculates the characters for each orbital, finds the irreducible representations, and uses selection rules to find which optical transitions are allowed. The capabilities of ADAQ-SYM are demonstrated on several defects in diamond and 4H-SiC. The symmetry analysis explains the different zero phonon line (ZPL) polarization of the hk and kh divacancies in 4H-SiC.

cond-mat.mtrl-sci↗

arXiv2023

Na in Diamond: High Spin Defects Revealed by the ADAQ High-Throughput Computational Database

Color centers in diamond are at the forefront of the second quantum revolution. A handful of defects are in use, and finding ones with all the desired properties for quantum applications is arduous. By using high-throughput calculations, we screen 21607 defects in diamond and collect the results in the ADAQ database. Upon exploring this database, we find not only the known defects but also several unexplored defects. Specifically, defects containing sodium stand out as particularly relevant because of their high spins and predicted improved optical properties compared to the NV center. Hence, we studied these in detail, employing high-accuracy theoretical calculations. The single sodium substitutional (Na$\mathrm{_C}$) has various charge states with spin ranging from 0.5 to 1.5, ZPL in the near-infrared, and a high Debye-Waller factor, making it ideal for biological quantum applications. The sodium vacancy (NaV) has a ZPL in the visible region and a potential rare spin-2 ground state. Our results show sodium implantation yields many interesting spin defects that are valuable additions to the arsenal of point defects in diamond studied for quantum applications.

cond-mat.mtrl-sci↗

arXiv2023

The Chlorine Vacancy in 4H-SiC: An NV-like Defect With Telecom Emission

The diamond nitrogen vacancy (NV) center remains an ever increasing topic of interest. At present, it is considered an ideal example of a solid-state qubit applicable in quantum communication, computing, and sensing alike. With its success, the search for defects that share or improve upon its advantageous features is an ongoing endeavor. By performing large-scale high-throughput screening of 52600 defects in 4H silicon carbide (SiC), we identify a collection of NV-like color-centers of particular interest. From this list, the single most promising candidate consists of a silicon vacancy and chlorine substituted on the carbon site, and is given the name of the chlorine vacancy (ClV) center. Through high-accuracy first-principle calculations, we confirm that the ClV center is similar to the NV center in diamond in its local structure and shares many qualitative and quantitative features in the electronic structure and spin properties. In contrast to the NV center, however, the ClV center in SiC exhibits emission in the telecom range near the C-band.

cond-mat.mtrl-sci↗

arXiv2023

Absorption $\textit{versus}$ Adsorption: High-Throughput Computation of Impurities in 2D Materials

Doping of a two-dimensional (2D) material by impurity atoms occurs \textit{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 \texttt{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. On the contrary, 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.

cond-mat.mtrl-sci↗

arXiv2022

Exhaustive characterization of modified Si vacancies in 4H-SiC

The negatively charged silicon vacancy ($\mathrm{V_{Si}^-}$) 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 antisite ($\mathrm{C_{Si}}$) 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 $\mathrm{V_{Si}^-+C_{Si}}$ 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.

cond-mat.mtrl-sci↗