409 citations · 1.1k across the 33 of their papers we have counts for
39 papers
Towards Dynamic Top- Simple Shortest Paths
Gianlorenzo D'Angelo, Andrea D'Ascenzo, Mattia D'Emidio +2
Computing the top- \textit{simple} shortest paths between two vertices of a graph, i.e., solving the P-KSSP problem, is a fundamental primitive in graph analytics. In modern sce…
Prescreening Point Defects in Semiconductors With Machine Learning
Paul Karlsson, Joel Davidsson, Rickard Armiento
High-throughput calculations using density-functional theory (DFT) are commonly used to explore point defects for applications in power electronics and quantum technologies. There…
Large spin splitting metallic altermagnets from machine-learned design rules
Ali Sufyan, Brahim Marfoua, J. Andreas Larsson +2
Altermagnets combine compensated magnetic order with momentum-dependent spin splitting, providing spin-polarized electronic states without a net magnetization. Metallic -wave al…
Color Centers in Cubic Boron Nitride
William Stenlund, Joel Davidsson, Viktor Ivády +2
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…
Symmetry-restricted energy landscapes as a benchmark for machine learned interatomic potentials
Abhijith S Parackal, Rickard Armiento, Florian Trybel
Machine learned interatomic potentials (MLIPs) are becoming a standard method for DFT-level accurate molecular dynamics simulation and large-scale studies of crystal energetics. In…
Screening 39 billion protostructures for materials discovery
Abhijith S Parackal, Florian Trybel, Felix Andreas Faber +1
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 tha…
High-Throughput Quantification of Altermagnetic Band Splitting
Ali Sufyan, Brahim Marfoua, J. Andreas Larsson +2
Altermagnetism represents a recently established class of collinear magnetism that combines zero net magnetization with momentum-dependent spin polarization, enabled by symmetry co…
High-Throughput Exploration of NV-like Color Centers Across Host Materials
Oscar Groppfeldt, Joel Davidsson, Rickard Armiento
Point defects in semiconductors offer a promising platform for advancing quantum technologies due to their localized energy states and controllable spin properties. Prior research…
WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry
Filip Ekström Kelvinius, Oskar B. Andersson, Abhijith S. Parackal +3
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…
Theoretical characterization of NV-like defects in 4H-SiC using ADAQ with the SCAN and r2SCAN meta-GGA functionals
Ghulam Abbas, Oscar Bulancea-Lindvall, Joel Davidsson +2
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 lac…
Predicting the Curie temperature in substitutionally disordered alloys using a first-principles based model
Marian Arale Brännvall, Rickard Armiento, Björn Alling
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 C…
Temperature dependence of the AB-lines and Optical Properties of the Carbon-Antisite Vacancy Pair in 4H-SiC
Oscar Bulancea-Lindvall, Joel Davidsson, Ivan G. Ivanov +4
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 g…
Evaluating and improving the predictive accuracy of mixing enthalpies and volumes in disordered alloys from universal pre-trained machine learning potentials
Luis Casillas-Trujillo, Abhijith S. Parackal, Rickard Armiento +1
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 calcul…
Predicting the Curie temperature of magnetic materials with automated calculations across chemistries and structures
Marian Arale Brännvall, Gabriel Persson, Luis Casillas-Trujillo +2
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…
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Matthew L. Evans, Johan Bergsma, Andrius Merkys +56
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enh…
Identifying Crystal Structures Beyond Known Prototypes from X-ray Powder Diffraction Spectra
Abhijith S. Parackal, Rhys E. A. Goodall, Felix A. Faber +1
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…
ADAQ-SYM: Automated Symmetry Analysis of Defect Orbitals
William Stenlund, Joel Davidsson, Viktor Ivády +2
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…
Na in Diamond: High Spin Defects Revealed by the ADAQ High-Throughput Computational Database
Joel Davidsson, William Stenlund, Abhijith S Parackal +2
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 applic…
The Chlorine Vacancy in 4H-SiC: An NV-like Defect With Telecom Emission
Oscar Bulancea-Lindvall, Joel Davidsson, Rickard Armiento +1
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 co…
Absorption Adsorption: High-Throughput Computation of Impurities in 2D Materials
Joel Davidsson, Fabian Bertoldo, Kristian S. Thygesen +1
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. T…
Exhaustive characterization of modified Si vacancies in 4H-SiC
Joel Davidsson, Rohit Babar, Danial Shafizadeh +4
The negatively charged silicon vacancy () in silicon carbide is a well-studied point defect for quantum applications. At the same time, a closer inspection of en…
Predicting properties of hard-coating alloys using ab-initio and machine learning methods
H. Levämäki, F. Tasnadi, D. G. Sangiovanni +3
Accelerated design of novel hard coating materials requires state-of-the-art computational tools, which include data-driven techniques, building databases, and training machine lea…
Graph-based machine learning beyond stable materials and relaxed crystal structures
Filip Ekström, Rickard Armiento, Fredrik Lindsten
There has been a recent surge of interest in using machine learning to approximate density functional theory (DFT) in materials science. However, many of the most performant models…
Rapid Discovery of Stable Materials by Coordinate-free Coarse Graining
Rhys E. A. Goodall, Abhijith S. Parackal, Felix A. Faber +2
A fundamental challenge in materials science pertains to elucidating the relationship between stoichiometry, stability, structure, and property. Recent advances have shown that mac…