arXiv subjects

Kai Nordlund

Publications and source records attributed to Kai Nordlund.

At least 19 recordsLinked to original sources

arXiv2026

Effect of Near-surface Thermal Spikes on Radiation Hardness of Gallium Oxide

Gallium oxide (Ga$_{2}$O$_{3}$) stands out as an extraordinary high radiation-tolerant semiconductor, because its lattice displacements induce polymorph transitions, holding material crystalline instead of leading to amorphization. Meanwhile, under extremely severe irradiation conditions many crystals become amorphous, often starting from surfaces where the translation symmetry breaks. Here, we show that the surface amorphization may prevail over the crystallisation in Ga$_{2}$O$_{3}$, however only if the mass and energy of irradiated ions produce sufficiently dense heat spikes in the immediate vicinity of the free surface. Applying machine-learned molecular dynamics simulations together with experimental broad-beam and focused ion-beam irradiations, we conclude that the presence of the free surface enables asymmetric displacements of Ga and O atoms, leading to a local non-stoichiometry. Consequently, when the affected cascade volume is sufficiently large, this compositional imbalance suppresses recrystallization and promotes amorphization. As such, our results are ready to use for tailoring irradiation conditions to either prevent or induce surface amorphization, depending on the requirements of the intended applications in Ga$_{2}$O$_{3}$ or other compound semiconductors.

cond-mat.mtrl-sci↗

arXiv2026

A General-Purpose and Efficient Machine-Learned Potential for SiC from Ambient to Extreme Environments

Silicon carbide (SiC) polymorphs are widely employed as nuclear materials, mechanical components, and wide-bandgap semiconductors. The rapid advancement of SiC-based applications has been complemented by computational modeling studies, including both ab initio and classical atomistic approaches. In this work, we develop a computationally efficient, general-purpose machine-learned interatomic potential (ML-IAP) capable of multimillion-atom molecular dynamics simulations over microsecond timescales. Using the ML-IAP, we map a broad pressure-temperature phase diagram and the threshold displacement energy distributions for the 2H and 3C polymorphs. Across a benchmark covering conditions from ambient to extreme, including high-pressure/high-temperature states and high-energy cascade damage, tabGAP provides a favorable balance of accuracy, robustness, transferability, and computational cost among the tested empirical and ML-IAPs.

cond-mat.mtrl-sci↗

arXiv2026

Surface-mediated reduction of ion-irradiation-induced damage in tungsten revealed by advanced ion channeling analysis

Tungsten is a leading candidate material for plasma-facing components in future fusion reactors. In this work, we integrate advanced ion channeling analysis with large-scale molecular dynamics simulations to uncover a pronounced surface-mediated reduction of radiation damage in single-crystal tungsten at elevated temperatures. We demonstrate how our unique analysis method can clearly resolve a dislocation-free zone near the surface and a transition region with suppressed defect density before reaching the bulk value. A possible explanation for the strong surface effect at elevated temperatures can be obtained by considering the coherent drift motion of dislocation loops toward the surface.

cond-mat.mtrl-sci↗

arXiv2025

Beyond dpa: an atomistic framework for a quantitative description of radiation damage in YBa2Cu3O7

Radiation damage in high-temperature cuprate superconductors represents one of the main technological challenges for their deployment in harsh environments, such as fusion reactors and accelerator facilities. Their complex crystal structure makes modeling irradiation effects in this class of materials a particularly demanding task, for which existing damage models remain inadequate. In this work, we develop an atomistic-based approach for describing primary radiation damage in YBa2Cu3O7, by coupling Molecular Dynamics and Binary Collision Approximation simulations in a way that makes them complementary. When integrated with Primary Knock-on Atom spectra obtained from Monte Carlo codes, our results establish a framework for multiscale modeling of radiation damage, enabling quantitative estimates of several damage descriptors, such as defect production, defect clustering, and the effective damaged volume for any specific irradiation conditions where collision cascades dominate. This computational approach is suitable for the prediction of irradiation effects in any complex functional oxide, with applications ranging from aerospace to nuclear fusion and high-energy physics.

cond-mat.supr-con↗

arXiv2025

Spontaneous damage annealing reactions as a possible source of low energy excess in semiconductor detectors

In semiconductor detectors designed for capturing dark matter particles or neutrinos, when the detection threshold is constantly improved to increasingly low energies, an "excess" signal of apparent energy release events below a few hundred eV is observed in several different kinds of detectors. This becomes a big obstacle to the observation of actual dark matter signals, hindering the detectors' sensitivity for rare events in this energy range. Using atomistic simulations with a classical thermostat and a quantum thermal bath, we show that this kind of signal is consistent with energy release from long-term annealing events of complex defects that can be formed by any kind of nuclear recoil radiation events. Such energy releases are shown to have a very similar exponential dependence on energy release magnitudes as that observed in experiments. By detailed analysis of the annealing events, we show that crossing very low energy barriers can trigger larger energy releases in an avalanche-like effect. This explains why large energy release events can occur even down to cryogenic temperatures, where the significant migration of point defects in silicon is hardly ever possible.

cond-mat.mtrl-sci↗

arXiv2025

Radiation damage and phase stability of Al$_x$CrCuFeNi$_y$ alloys using a machine-learned interatomic potential

We develop a machine-learned interatomic potential for AlCrCuFeNi high-entropy alloys (HEA) using a diverse set of structures from density functional theory calculated including magnetic effects. The potential is based on the computationally efficient tabulated version of the Gaussian approximation potential method (tabGAP) and is a general-purpose model for molecular dynamics simulation of the HEA system, with additional emphasis on radiation damage effects. We use the potential to study key properties of AlCrCuFeNi HEAs at different compositions, focusing on the FCC/BCC phase stability. Monte Carlo swapping simulations are performed to understand the stability and segregation of the HEA and reveal clear FeCr and Cu segregation. Close to equiatomic composition, a transition from FCC to BCC is detected, following the valence electron concentration stability rule. Furthermore, we perform overlapping cascade simulations to investigate radiation damage production and tolerance. Different alloy compositions show significant differences in defect concentrations, and all alloy compositions show enrichment of some elements in or around defects. We find that, generally, a lower Al content corresponds to lower defect concentrations during irradiation. Furthermore, clear short-range ordering is observed as a consequence of continued irradiation.

cond-mat.mtrl-sci↗

arXiv2025

Repulsive interatomic potentials calculated at three levels of theory

The high-energy repulsive interaction between nuclei at distances much smaller than the equilibrium bond length is the key quantity determining the nuclear stopping power and atom scattering in keV and MeV radiation events. This interaction is traditionally modeled within orbital-free density functional theory with frozen atomic electron densities, following the Ziegler-Biersack-Littmark (ZBL) model. In this work, we calculate atom pair specific repulsive interatomic potentials with the ZBL model, and compare them to two kinds of quantum chemical calculations - second-order Møller-Plesset perturbation theory in flexible Gaussian basis sets as well as density functional theory with numerical atomic orbital basis sets - which go well beyond the limitations in the ZBL model, allowing the density to relax in the calculations. We show that the repulsive interatomic potentials predicted by the two quantum chemical models agree within $\sim$ 1% for potential energies above 30 eV, while the ZBL pair-specific potentials and universal ZBL potentials differ much more from either of these calculations. We provide new pair-specific fits of the screening functions in terms of 3 exponentials to the calculations for all pairs $Z_1$-$Z_2$ for $1 \leq Z_i \leq 92$, and show that they agree within $\sim 2$% with the raw data. We use the new potentials to simulate ion implantation depth profiles in single crystalline Si and show very good agreement with experiment. However, we also show that under channeling conditions, the attractive part of the potential can affect the depth profiles. The full data sets of all the calculated interatomic potentials as well as analytic fits to the data are shared as open access.

physics.comp-ph↗

arXiv2024

Threshold displacement energies in refractory high-entropy alloys

Refractory high-entropy alloys show promising resistance to irradiation, yet little is known about the fundamental nature of radiation-induced defect formation. Here, we simulate threshold displacement energies in equiatomic MoNbTaVW using an accurate machine-learned interatomic potential, covering the full angular space of crystal directions. The effects of local chemical ordering is assessed by comparing results in randomly ordered and short-range-ordered MoNbTaVW. The average threshold displacement energy in the random alloy is $44.3 \pm 0.15$ eV and slightly higher, $48.6 \pm 0.15$ eV, in the short-range-ordered alloy. Both are significantly lower than in any of the constituent pure metals. We identify the mechanisms of defect creation and find that they are mainly dependent on the masses of the recoiling and colliding elements. Low thresholds are generally found when heavy atoms (W, Ta) displace and replace the lightest atoms (V). The average threshold energies when separated by recoiling element are consequently ordered inversely according to their mass, opposite to the trend in the pure metals where W has by far the highest thresholds. However, the trend in the alloy is reversed when considering the cross sections for defect formation in electron irradiation, due to the mass-dependent recoil energies from the electrons.

cond-mat.mtrl-sci↗

arXiv2024

Fast and accurate machine-learned interatomic potentials for large-scale simulations of Cu, Al and Ni

Machine learning (ML) has become widely used in the development of interatomic potentials for molecular dynamics simulations. However, most ML potentials are still much slower than classical interatomic potentials and are usually trained with near equilibrium simulations in mind. In this work, we develop ML potentials for Cu, Al and Ni using the Gaussian approximation potential (GAP) method. Specifically, we create the low-dimensional tabulated versions (tabGAP) of the potentials, which allow for two orders of magnitude higher computational efficiency than the GAPs, enabling simulations of large multi-million atomic systems. The ML potentials are trained using diverse curated databases of structures and include fixed external repulsive potentials for short-range interactions. The potentials are extensively validated and used to simulate a wide range of fundamental materials properties, such as stacking faults and threshold displacement energies. Furthermore, we use the potentials to simulate single-crystal uniaxial compressive loading in different crystal orientations with both pristine simulation cells and cells containing pre-existing defects.

cond-mat.mtrl-sci↗

arXiv2024

Probing the dark matter velocity distribution via daily modulation

We consider dark matter velocity distributions with an anisotropic component, and analyze how the velocity structure can be probed in a solid state ionization detector with no directional detection capability using a daily modulation effect due to the anisotropic response function of the target. We show that with an energy resolution of < 10 eV it is possible to identify the presence of an anisotropic component consistent with observations for sub-GeV dark matter, and that introduction of daily modulation information substantially improves the sensitivity in a narrow mass range.

hep-ph↗

arXiv2024

Crystallization Instead of Amorphization in Collision Cascades in Gallium Oxide

Disordering of solids typically leads to amorphization, but polymorph transitions, facilitated by favorable atomic rearrangements, may temporarily help to maintain long-range periodicity in the solid state. In far-from-equilibrium situations, such as atomic collision cascades, these rearrangements may not necessarily follow a thermodynamically gainful path, but may be kinetically limited. In this Letter, we focused on such crystallization instead of amorphization in collision cascades in gallium oxide (\ce{Ga2O3}). We determined the disorder threshold for irreversible $β$-to-$γ$ polymorph transition and explained why it results in elevating energy to that of the $γ$-polymorph, which exhibits the highest polymorph energy in the system below the amorphous state. Specifically, we demonstrate that upon reaching the disorder transition threshold, the \ce{Ga}-sublattice kinetically favors transitioning to the $γ$-like configuration, requiring significantly less migration for \ce{Ga} atoms to reach the lattice sites during post-cascade processes. As such, our data provide a consistent explanation of this remarkable phenomenon and can serve as a toolbox for predictive multi-polymorph fabrication.

cond-mat.mtrl-sci↗

arXiv2024

Threshold displacement energy map of Frenkel pair generation in $\rm Ga_2O_3$ from machine-learning-driven molecular dynamics simulations

$β$ phase gallium oxide ($β$-$\rm Ga_2O_3$) demonstrates tremendous potential for electronics applications and offers promising prospects for integration into future space systems with the necessity of high radiation resistance. Therefore, a comprehensive understanding of the threshold displacement energy (TDE) and the radiation-induced formation of Frenkel pairs (FPs) in this material is vital but has not yet been thoroughly studied. In this work, we performed over 5,000 molecular dynamics simulations using our machine-learning potentials to determine the TDE and investigate the formation of FPs. The average TDEs for the two Ga sites, Ga1 (tetrahedral site) and Ga2 (octahedral site), are 22.9 and 20.0 eV, respectively. While the average TDEs for the three O sites are nearly uniform, ranging from 17.0 to 17.4 eV. The generated TDE maps reveal significant differences in displacement behavior between these five atomic sites. Our developed defect identification methods successfully categorize various types of FPs in this material, with more than ten types of Ga FPs being produced during our simulations. O atoms are found to form two main types of FPs and the O split interstitial site on O1 site is most common. Finally, the recombination behavior and barriers of Ga and O FPs indicate that the O FP has a higher possibility of recovery upon annealing. Our findings provide important insights into the studies of radiation damage and defects in $\rm Ga_2O_3$ and can contribute to the design and development of $\rm Ga_2O_3$-based devices

cond-mat.mtrl-sci↗

arXiv2023

Analysis of lattice locations of deuterium in tungsten and its application for predicting deuterium trapping conditions

Retention of hydrogen isotopes (protium, deuterium and tritium) in tungsten is one of the most severe issues in design of fusion power plants, since significant trapping of tritium may cause exceeding radioactivity safety limits in future reactors. Hydrogen isotopes in tungsten can be detected using the nuclear reaction analysis method in channeling mode (NRA/C). However, the information hidden within the experimental spectra is subject to interpretation. In this work, we propose the methodology to interpret the response of the experimental NRA/C spectra to the specific lattice locations of deuterium by simulations of the NRA/C spectra from atomic structures of deuterium lattice locations as obtained from the first principles calculations. We show that trapping conditions, i.e., states of local crystal structures retaining deuterium, affect the lattice locations of deuterium and the change of lattice locations can be detected by ion channeling method. By analyzing the experimental data, we are able to determine specific information on the deuterium trapping conditions, including the number of deuterium atoms trapped by one vacancy as well as the presence of impurity atoms along with deuterium in vacancies.

cond-mat.mtrl-sci↗

arXiv2023

Efficient atomistic simulations of radiation damage in W and W-Mo using machine-learning potentials

The Gaussian approximation potential (GAP) is an accurate machine-learning interatomic potential that was recently extended to include the description of radiation effects. In this study, we seek to validate a faster version of GAP, known as tabulated GAP (tabGAP), by modelling primary radiation damage in 50-50 W-Mo alloys and pure W using classical molecular dynamics. We find that W-Mo exhibits a similar number of surviving defects as in pure W. We also observe W-Mo to possess both more efficient recombination of defects produced during the initial phase of the cascades, and in some cases, unlike pure W, recombination of all defects after the cascades cooled down. Furthermore, we observe that the tabGAP is two orders of magnitude faster than GAP, but produces a comparable number of surviving defects and cluster sizes. A small difference is noted in the fraction of interstitials that are bound into clusters.

cond-mat.mtrl-sci↗

arXiv2023

Complex $\mathrm{Ga}_{2}\mathrm{O}_{3}$ Polymorphs Explored by Accurate and General-Purpose Machine-Learning Interatomic Potentials

$\mathrm{Ga}_{2}\mathrm{O}_{3}$ is a wide-bandgap semiconductor of emergent importance for applications in electronics and optoelectronics. However, vital information of the properties of complex coexisting $\mathrm{Ga}_{2}\mathrm{O}_{3}$ polymorphs and low-symmetry disordered structures is missing. In this work, we develop two types of kernel-based machine-learning Gaussian approximation potentials (ML-GAPs) for $\mathrm{Ga}_{2}\mathrm{O}_{3}$ with high accuracy for $β$/$κ$/$α$/$δ$/$γ$ polymorphs and generality for disordered stoichiometric structures. We release two versions of interatomic potentials in parallel, namely soapGAP and tabGAP, for excellent accuracy and exceeding speedup, respectively. We systematically show that both the soapGAP and tabGAP can reproduce the structural properties of all the five polymorphs in an exceptional agreement with ab initio results, meanwhile boost the computational efficiency with $5\times10^{2}$ and $2\times10^{5}$ computing speed increases compared to density functional theory, respectively. The results show that the liquid-solid phase transition proceeds in three different stages, a "slow transition", "fast transition" and "only Ga migration". We show that this complex dynamics can be understood in terms of different behavior of O and Ga sublattices in the interfacial layer.

cond-mat.mtrl-sci↗

arXiv2023

Daily and annual modulation rate of low mass dark matter in silicon detectors

Low threshold detectors with single-electron excitation sensitivity to nuclear recoil events in solid-state detectors are also sensitive to the crystalline structure of the target and, therefore, to the recoil direction via the anisotropic energy threshold for defect creation in the detector material. We investigate this effect and the resulting daily and annual modulation of the observable event rate for dark matter mass range from 0.2 to 5 GeV/c$^{2}$ in a silicon detector. We show that the directional dependence of the threshold energy and the motion of the laboratory result in modulation of the event rate which can be utilized to enhance the sensitivity of the experiment. We demonstrate that the spin-independent interaction rate in silicon is significant for both high and low dark matter masses. For low-mass dark matter, we show that the average interaction rate in silicon is larger than germanium, making silicon an important target for identifying dark matter from backgrounds. We find 8 and 12 hours periodicity in the time series of event rates for silicon detector due to the 45-degree symmetry in the silicon crystal structure.

hep-ph↗

arXiv2022

Identification of the low energy excess in dark matter searches with crystal defects

An excess of events of unknown origin at low energies below 1 keV has been observed in multiple low-threshold dark matter detectors. Depending on the target material, nuclear recoil events at these energies may cause lattice defects, in which case a part of the true recoil energy is stored in the defect and not observed in the phonon detector. If the threshold for defect creation is sharp, this effect leads to a prominent feature in the observed recoil spectrum. Electronic recoils at low energies do not create defects and therefore the feature in the observed spectrum is not expected in that case. We propose to use the sharp defect creation threshold of diamond to test if the low energy events are due to nuclear recoils. Based on simulated data we expect the nuclear recoil bump in the observed spectrum to be visible in diamond with just ~0.1 gram days of exposure.

hep-ph↗

arXiv2022

Energy loss due to defect creation in solid state detectors

The threshold displacement energy in solid state detector materials varies from several eV to ~100 eV. If a stable or long lived defect is created as a result of a nuclear recoil event, some part of the recoil energy is stored in the deformed lattice and is therefore not observable in a phonon detector. Thus, an accurate model of this effect is necessary for precise calibration of the recoil energy measurement in low threshold phonon detectors. Furthermore, the sharpness of the defect creation threshold varies between materials. For a hard material such as diamond, the sharp threshold will cause a sudden onset of the energy loss effect, resulting in a prominent peak in the observed recoil spectrum just below the threshold displacement energy. We describe how this effect can be used to discriminate between nuclear and electron recoils using just the measured recoil spectrum.

physics.ins-det↗