arXiv subjects

Johan Klarbring

Publications and source records attributed to Johan Klarbring.

18 recordsLinked to original sources

arXiv2026

Thermal history controls the optoelectronic response of lead halide perovskites through structure and dynamics

Lead halide perovskites are promising optoelectronic materials for photovoltaics, light emission and detection. Their efficiencies in PV now approach the detailed-balance limit, leaving stability as the principal barrier. The intrinsic instabilities studied to date centre on ionic motion within a fixed, homogeneous lattice. Here we identify a further source of intrinsic structural instability, hidden in the lattice dynamics. Mapping caesium, methylammonium and formamidinium-based compositions with Cl, Br, I and mixed X-sites through all accessible phases, using single crystal X-ray and neutron diffuse scattering, machine-learning-assisted molecular dynamics, a phenomenological octahedral tilt model and hyperspectral photoluminescence, we find that nearly every composition hosts equilibrium local structural fluctuations: dynamic nanodomains of correlated octahedral tilts, a few nanometres in size, that locally break the crystallographic symmetry. Three complementary levers control them. The A-site cation sets their symmetry, shape and anisotropy, from sparse, isotropic and tetragonal in formamidinium-based compositions to dense, anisotropic and orthorhombic in nominally cubic caesium-based ones, the most locally disordered we studied. The halide controls the dynamic disorder and the phase-transition sequence. Thermal history is the third: different ramp rates drive nominally identical compositions into distinct crystallographic phases, each with its own hidden local order. In MAPbI3, the heating rate alone changes the photoluminescence quantum efficiency across the phase transition. Because these transitions lie within device operating ranges, from terrestrial thermal cycling to the extremes of space, thermal history may shape the local structure, and hence the optoelectronic response, throughout fabrication and operation, establishing it as a design variable alongside composition.

cond-mat.mtrl-sci↗

arXiv2026

Barocaloric phase transformation from data efficient fine-tuning of machine learned interatomic potentials

Solid-state cooling based on the barocaloric (BC) effect has emerged as promising environmentally friendly prospective alternative to conventional vapor-compression refrigeration. The search for suitable BC materials relies on efficient atomistic simulations of their phase behavior. Machine-learned interatomic potentials (MLIPs) enable such simulations at near density functional theory (DFT) accuracy, but generating the required DFT training data remains computationally demanding, which motivates development of strategies that reduce the amount of data needed to train accurate models. In this work, we use a prototypical BC material, ammonium sulfate, as a model system and investigate how small a training set can be while still reproducing the temperature-driven structural phase transformation that underlies its BC response. We train a series of MLIPs based on the MACE architecture using three strategies: training from scratch, and naive- and multihead replay fine-tuning of the MACE-MPA-0 foundation model. These strategies are evaluated on their ability to reproduce the phase transformation of ammonium sulfate in molecular dynamics simulations across a range of training-set sizes. We find that, while the MACE-MPA-0 foundation model itself fails to reproduce the transformation, and models trained from scratch break down for small datasets, fine-tuned models reproduce the transformation using as few as 5 to 10 60-atom DFT configurations. Both fine-tuning protocols yield similarly accurate results for ammonium sulfate, but we also find some indications that multihead replay fine-tuning is more robust on configurations outside the fine-tuning domain. Exploiting this data efficiency, we further show that models can be trained on small datasets and the hybrid-DFT level, and that some form of inclusion of dispersion correction is necessary to describe the phase behavior correctly.

cond-mat.mtrl-sci↗

arXiv2026

Kinetically Arrested Twin-Domain State in Formamidinium Lead Iodide

Hybrid lead halide perovskites exhibit a delicate interplay between average crystallographic symmetry, local structural disorder and A-site orientational dynamics, giving rise to unusual vibrational and electronic behaviour. Here, we combine large-scale molecular dynamics with a density-functional-theory-accurate machine learning force field to resolve the structural dynamics of perovskites across mesoscopic length scales. In formamidinium lead iodide FAPbI$_{3}$, we identify a high-temperature $\alpha$ phase with dynamic local order and correlated tilt nanodomains, an ordered $\gamma$ phase with long-range $a^{+}a^{+}a^{+}$ tilt coherence, and, below $\sim$100 K, a history-dependent $\gamma'$ state consisting of locally $\gamma$-like nanoscale regions separated by sharp twin-like boundaries. This low-temperature disordered state is not a distinct bulk polymorph, but a kinetically arrested metastable twin-domain network selected by the interplay between shallow tilt energetics and slowing FA reorientation. This picture provides a consistent explanation for the low-temperature diffuse scattering features observed experimentally, and accounts for the broadened low-energy vibrational response found in the simulations. Furthermore, this unique structural landscape imprints a spatially varying electronic disorder that directly impacts macroscopic optoelectronic properties, evidenced by an anomalous increase in the Urbach energy at low temperatures. Our results reconcile the debated low-temperature behaviour of FAPbI$_{3}$ in terms of competition between ordered and arrested structural states, and show more broadly that in hybrid perovskites the organic cation can actively select the macroscopic structural and electronic response through its reorientation kinetics, placing thermal history on equal footing with composition as a determinant of structural and optoelectronic properties.

cond-mat.mtrl-sci↗

arXiv2025

The diffusion-driven orthorhombic to tetragonal transition in YBa$_2$Cu$_3$O$_7$ derived with a machine learning interatomic potential

Defects in high temperature superconductors such as YBa$_2$Cu$_3$O$_7$ (YBCO) critically influence their superconducting behavior, as they substantially degrade or even suppress superconductivity. With the renewed interest in cuprates for next-generation superconducting magnets operating in radiation-harsh environments such as fusion reactors and particle accelerators, accurate atomistic modeling of defects and their dynamics has become essential. Here, we present a general-purpose machine-learning interatomic potential for YBCO, based on the Atomic Cluster Expansion (ACE) method and trained on Density Functional Theory (DFT) data, with particular emphasis on defects and their diffusion mechanisms. The potential is validated against DFT calculations of ground-state properties, defect formation energies of oxygen Frenkel pairs and diffusion barriers for their formation. Remarkably, the potential captures the diffusion-driven orthorhombic to tetragonal transition at elevated temperatures, a transformation that is difficult to describe with empirical potentials, elucidating how the formation of oxygen Frenkel pairs in the basal plane governs this order-disorder transition. The ACE potential introduced here enables large-scale, predictive atomistic simulations of defect dynamics and transport processes in YBCO, providing a powerful tool to explore its stability, performance, and functionality under realistic operating conditions. Moreover, this work proves that machine learning interatomic potentials are suitable for studies of quaternary oxides with complex chemistry.

cond-mat.mtrl-sci↗

arXiv2025

Phase Stability and Transformations in Lead Mixed Halide Perovskites from Machine Learning Force Fields

Lead halide perovskites (APbX$_3$) offer tunable optoelectronic properties but feature an intricate phase-stability landscape. Here we employ on-the-fly data collection and an equivariant message-passing neural-network potential to perform large-scale molecular dynamics of three prototypical perovskite systems: CsPbX$_3$, MAPbX$_3$, and FAPbX$_3$. Integrating these simulations with the PDynA analysis toolkit, we resolve both equilibrium phase diagrams and dynamic structural evolution under varying temperature and halide-mixing conditions. Our findings reveal that the A-site cation strongly modulates octahedral tilt modes and phase pathways: MA$^+$ effectively "forbids" the beta-to-gamma transition in MAPbX$_3$ by requiring extensive molecular rearrangements and crystal rotation, whereas the debated low-temperature phase in FAPbX$_3$ is best represented as an Im$\bar{3}$ cubic phase with $a^+a^+a^+$ tilts. Additionally, small changes in halide composition and arrangement $\unicode{x2013}$ from uniform mixing to partial segregation $\unicode{x2013}$ alter tilt correlations. Segregated domains can even foster anomalous tilting modes that impede uniform phase transformations. These results highlight the multi-scale interplay between cation environment and halide distribution, offering a rational basis for tuning perovskite architectures toward improved phase stability.

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arXiv2024

Point defect formation at finite temperatures with machine learning force fields

Point defects dictate the properties of many functional materials. The standard approach to modelling the thermodynamics of defects relies on a static description, where the change in Gibbs free energy is approximated by the internal energy. This approach has a low computational cost, but ignores contributions from atomic vibrations and structural configurations that can be accessed at finite temperatures. We train a machine learning force field (MLFF) to explore dynamic defect behaviour using $\mathrm{Te_i^{+1}}$ and $\textit{V}{\mathrm{_{Te}^{+2}}}$ in CdTe as exemplars. We consider the different entropic contributions (e.g., electronic, spin, vibrational, orientational, and configurational) and compare methods to compute the defect free energies, ranging from a harmonic treatment to a fully anharmonic approach based on thermodynamic integration. We find that metastable configurations are populated at room temperature and thermal effects increase the predicted concentration of $\mathrm{Te_i^{+1}}$ by two orders of magnitude -- and can thus significantly affect the predicted properties. Overall, our study underscores the importance of finite-temperature effects and the potential of MLFFs to model defect dynamics at both synthesis and device operating temperatures.

cond-mat.mtrl-sci↗

arXiv2024

Dynamic Nanodomains Dictate Macroscopic Properties in Lead Halide Perovskites

Empirical A-site cation substitution has advanced the stability and efficiency of hybrid organic-inorganic lead halide perovskites solar cells and the functionality of X-ray detectors. Yet, the fundamental mechanisms underpinning their unique performance remain elusive. This multi-modal study unveils the link between nanoscale structural dynamics and macroscopic optoelectronic properties in these materials by utilising X-ray diffuse scattering, inelastic neutron spectroscopy and optical microscopy complemented by state-of-the-art machine learning-assisted molecular dynamics simulations. Our approach uncovers the presence of dynamic, lower-symmetry local nanodomains embedded within the higher-symmetry average phase in various perovskite compositions. The properties of these nanodomains are tunable via the A-site cation selection: methylammonium induces a high density of anisotropic, planar nanodomains of out-of-phase octahedral tilts, while formamidinium favours sparsely distributed isotropic, spherical nanodomains with in-phase tilting, even when crystallography reveals cubic symmetry on average. The observed variations in the properties of dynamic nanodomains are in agreement with our simulations and are directly linked to the differing macroscopic optoelectronic and ferroelastic behaviours of these compositions. By demonstrating the influence of A-site cation on local nanodomains and consequently, on macroscopic properties, we propose leveraging this relationship to engineer the optoelectronic response of these materials, propelling further advancements in perovskite-based photovoltaics, optoelectronics, and X-ray imaging.

cond-mat.mtrl-sci↗

arXiv2024

Anisotropic electron-phonon interactions in 2D lead-halide perovskites

Two-dimensional hybrid organic-inorganic metal halide perovskites offer enhanced stability for perovskite-based applications. Their crystal structure's soft and ionic nature gives rise to strong interactions between charge carriers and ionic rearrangements. Here, we investigate the interaction of photo-generated electrons and ionic polarizations in single-crystal 2D perovskite butylammonium lead iodide, varying the inorganic lammelae thickness in the 2D single crystals. We determined the directionality of the transition dipole moments of the relevant phonon modes (in the 0.3-3 THz range) by angle-and-polarization dependent THz transmission measurements. We find a clear anisotropy of the in-plane photoconductivity, with a 10% reduction along the axis parallel with the transition dipole moment of the most strongly coupled phonon. Detailed calculations, based on Feynman polaron theory, indicate that the anisotropy originates from directional electron-phonon interactions.

cond-mat.mtrl-sci↗

arXiv2024

Na Vacancy Driven Phase Transformation and Fast Ion Conduction in W-doped Na$_3$SbS$_4$ from Machine Learning Force Fields

Solid-state sodium batteries require effective electrolytes that conduct at room temperature. The Na$_3$SbS$_4$ (Pn = P, Sb; Ch = S, Se) family have been studied for their high Na ion conductivity. The population of Na vacancies, which mediate ion diffusion in these materials, can be enhanced through aliovalent doping on the pnictogen site. To probe the microscopic role of extrinsic doping, and its impact on diffusion and phase stability, we trained a machine learning force field for Na$_{3-x}$W$_{x}$Sb$_{1-x}$S$_4$ based on an equivariant graph neural network. Analysis of large-scale molecular dynamics trajectories shows that an increased Na vacancy population stabilises the global cubic phase at lower temperatures with enhanced Na ion diffusion, and that the explicit role of the substitutional W dopants is limited. In the global cubic phase we observe large and long-lived deviations of atoms from the averaged symmetry, echoing recent experimental suggestions. Evidence of correlated Na ion diffusion is also presented that underpins the suggested superionic nature of these materials.

cond-mat.mtrl-sci↗

arXiv2023

Imperfections are not 0 K: free energy of point defects in crystals

Defects determine many important properties and applications of materials, ranging from doping in semiconductors, to conductivity in mixed ionic-electronic conductors used in batteries, to active sites in catalysts. The theoretical description of defect formation in crystals has evolved substantially over the past century. Advances in supercomputing hardware, and the integration of new computational techniques such as machine learning, provide an opportunity to model longer length and time-scales than previously possible. In this Tutorial Review, we cover the description of free energies for defect formation at finite temperatures, including configurational (structural, electronic, spin) and vibrational terms. We discuss challenges in accounting for metastable defect configurations, progress such as machine learning force fields and thermodynamic integration to directly access entropic contributions, and bottlenecks in going beyond the dilute limit of defect formation. Such developments are necessary to support a new era of accurate defect predictions in computational materials chemistry.

cond-mat.mtrl-sci↗

arXiv2023

Exploring Magnetism of Lead-free Halide Double Perovskites: A High-Throughput First-Principles Study

We have performed a comprehensive, first-principles high-throughput study of the magnetic properties of halide double perovskites, $Cs_2BB^\prime Cl_6$, with magnetic ions occupying one or both B and B$^\prime$ sites. Our findings indicate a general tendency for these materials to exhibit antiferromagnetic ordering with low N\'eel temperatures. At the same time, we reveal a few potential candidates that predicted to be ferromagnetic with relatively high Curie temperatures. Achieving ferromagnetic coupling might be feasible via simultaneously alloying at B and B$^\prime$ sites with magnetic 3d and non-magnetic 5d ions. With this approach, we discover that $Cs_2HgCrCl_6$, $Cs_2AgNiCl_6$ and $Cs_2AuNiCl_6$ have high Curie temperatures relative to their peers, with the latter two exhibiting half metallic behaviour. Further, this study illuminates the underpinning mechanism of magnetic exchange interactions in halide double perovskites, enabling a deeper understanding of their magnetic behaviour. Our findings, especially the discovery of the compounds with robust half-metallic properties and high Curie temperatures holds promise for potential applications in the field of spintronics.

cond-mat.mtrl-sci↗

arXiv2023

Structural Dynamics Descriptors for Metal Halide Perovskites

Metal halide perovskites have shown extraordinary performance in solar energy conversion technologies. They have been classified as "soft semiconductors" due to their flexible corner-sharing octahedral networks and polymorphous nature. Understanding the local and average structures continues to be challenging for both modelling and experiments. Here, we report the quantitative analysis of structural dynamics in time and space from molecular dynamics simulations of perovskite crystals. The compact descriptors provided cover a wide variety of structural properties, including octahedral tilting and distortion, local lattice parameters, molecular orientations, as well as their spatial correlation. To validate our methods, we have trained a machine learning force field (MLFF) for methylammonium lead bromide (CH$_3$NH$_3$PbBr$_3$) using an on-the-fly training approach with Gaussian process regression. The known stable phases are reproduced and we find an additional symmetry-breaking effect in the cubic and tetragonal phases close to the phase transition temperature. To test the implementation for large trajectories, we also apply it to 69,120 atom simulations for CsPbI$_3$ based on an MLFF developed using the atomic cluster expansion formalism. The structural dynamics descriptors and Python toolkit are general to perovskites and readily transferable to more complex compositions.

cond-mat.mtrl-sci↗

arXiv2023

Dynamic Local Structure in Caesium Lead Iodide: Spatial Correlation and Transient Domains

Metal halide perovskites are multifunctional semiconductors with tunable structures and properties. They are highly dynamic crystals with complex octahedral tilting patterns and strongly anharmonic atomic behaviour. In the higher temperature, higher symmetry phases of these materials, several complex structural features have been observed. The local structure can differ greatly from the average structure and there is evidence that dynamic two-dimensional structures of correlated octahedral motion form. An understanding of the underlying complex atomistic dynamics is, however, still lacking. In this work, the local structure of the inorganic perovskite CsPbI$_3$ is investigated using a new machine learning force field based on the atomic cluster expansion framework. Through analysis of the temporal and spatial correlation observed during large-scale simulations, we reveal that the low frequency motion of octahedral tilts implies a double-well effective potential landscape, even well into the cubic phase. Moreover, dynamic local regions of lower symmetry are present within both higher symmetry phases. These regions are planar and we report the length and timescales of the motion. Finally, we investigate and visualise the spatial arrangement of these features and their interactions, providing a comprehensive picture of local structure in the higher symmetry phases.

cond-mat.mtrl-sci↗

arXiv2022

Electronic structure of the magnetic halide double perovskites Cs2(Ag,Na)FeCl6 from first-principles

A family of magnetic halide double perovskites (HDPs) have recently attracted attention due to their potential to broaden application areas of halide double perovskites into e.g. spintronics. Up to date the theoretical modelling of these systems have relied on primitive approximations to the density functional theory (DFT). In this paper, we study structural, electronic and magnetic properties of the Fe$^{3+}$-containing HDPs Cs$_2$AgFeCl$_6$ and Cs$_2$NaFeCl$_6$ using a combination of more advanced DFT-based methods, including DFT+U, hybrid-DFT and treatments of various magnetic states. We examine the effect of varying the effective Hubbard parameter, U$_{eff}$, in DFT+U and the mixing-parameter, $\alpha$, in hybrid DFT on the electronic structure and structural properties. Our results reveal a set of localized Fe(d) states that are highly sensitive to these parameters. Cs$_2$AgFeCl$_6$ and Cs$_2$NaFeCl$_6$ are both antiferromagnets with Ne\'el temperatures well below room temperature and are thus in their paramagnetic (PM) state at the external conditions relevant to most applications. Therefore, we have examined the effect of disordered magnetism on the electronic structure of these systems and find that while Cs$_2$NaFeCl$_6$ is largely unaffected, Cs$_2$AgFeCl$_6$ shows significant renormalization of its electronic band structure.

cond-mat.mtrl-sci↗

arXiv2022

Phase stability of Fe from first-principles: atomistic spin dynamics coupled with ab initio molecular dynamics simulations and thermodynamic integration

The calculation of free energies from first principles in materials is a formidable task which enables the prediction of phase stability with high accuracy; these calculations are complicated in magnetic materials by the interplay of electronic, magnetic, and vibrational degrees of freedom. In this work, we show the feasibility and accuracy of the calculation of phase stability in magnetic systems with ab initio methods and thermodynamic integration by sampling the magnetic and vibrational phase space with coupled atomistic spin dynamics-ab initio molecular dynamics (ASD-AIMD) simulations [Stockem et al., PRL 121, 125902 (2018)], where energies and interatomic forces are calculated with density functional theory (DFT). We employ the method to calculate the phase stability of Fe at ambient pressure from 800 K up to 1800 K. The Gibbs free energy difference between fcc and bcc Fe at zero pressure as a function of temperature is calculated carrying out thermodynamic integration over temperature on the energies at the DFT level from ASD-AIMD, using a reference free energy difference calculated in the paramagnetic state at temperatures much higher than the magnetic transition temperatures with thermodynamic integration over stress-strain variables with disordered local moment (DLM)-AIMD simulations. We show the importance of the magnetic ordering temperature of bcc Fe on the $\alpha$ to $\gamma$ structural transition temperature, whereas the $\gamma$ to $\delta$ transition is well reproduced independently of the exchange interactions. The Gibbs free energy difference between the two structures is within 5 meV/atom from the CALPHAD estimate, and both transition temperatures are reproduced within 150 K. The present work paves the way to free energy calculations in magnetic materials from first principles with accuracy in the order of 1 meV/atom.

cond-mat.mtrl-sci↗

arXiv2020

Ab initio Determination of Phase Stabilities of Dynamically Disordered Solids: rotational C2 disorder in Li2C2

The temperature-induced orthorhombic to cubic phase transition in Li2C2 is a prototypical example of a solid to solid phase transformation between an ordered phase, which is well described within the phonon theory, and a dynamically disordered phase with rotating molecules, for which the standard phonon theory is not applicable. The transformation in Li2C2 happens from a phase with directionally ordered C2 dimers to a structure, where they are dynamically disorderd. We provide a description of this transition by employing ab initio molecular dynamics (AIMD) based stress-strain thermodynamic integration on a deformation path that connects the ordered and dynamically disordered phases. The free energy difference between the two phases is obtained. The entropy that stabilizes the dynamically disordered cubic phase is captured by the behavior of the stress on the deformation path. We also show that a combination of the stress-strain thermodynamic integration and machine learning force field methodologies appears as a promising path in studies of dynamically disordered materials.

cond-mat.mtrl-sci↗

arXiv2019

Anharmonicity and Ultra-Low Thermal Conductivity in Lead-Free Halide Double Perovskites

The lead-free halide double perovskite class of materials offers a promising venue for resolving issues related to toxicity of Pb and long-term stability of the lead-containing halide perovskites. We present a first-principles study of the lattice vibrations in Cs$_2$AgBiBr$_6$ , the prototypical compound in this class, and show that the lattice dynamics of Cs$_2$AgBiBr$_6$ is highly anharmonic, largely in regards to tilting of AgBr$_6$ and BiBr$_6$ octahedra. Using an energy and temperature dependent phonon spectral function, we then show how the experimentally observed cubic-to-tetragonal phase transformation is caused by the collapse of a soft phonon branch. We finally reveal that the softness and anharmonicity of Cs$_2$AgBiBr$_6$ yield an ultra-low thermal conductivity, unexpected of high symmetry cubic structures.

cond-mat.mtrl-sci↗

arXiv2018

Low energy paths for octahedral tilting in inorganic halide perovskites

Instabilities relating to cooperative octahedral tilting is common in materials with perovskite structures, and in particular in the sub class of halide perovskites. In this work, the energetics of octahedral tilting in the inorganic metal halide perovskites CsPbI$_3$ and CsSnI$_3$ are investigated using first-principles density functional theory calculations. Several low energy paths between symmetry equivalent variants of the stable orthorhombic (\textit{Pnma}) perovskite variant are identified and investigated. The results are in favor of the presence of dynamic disorder in the octahedral tilting phase transitions of inorganic halide perovskites. In particular, one specific type of path, corresponding to an out-of-phase "tilt switch", is found to have significantly lower energy barrier than the others, which indicates the existence of a temperature range where the dynamic fluctuations of the octahedra follow only this type of path. This could produce a time averaged structure corresponding to the intermediate tetragonal (\textit{P4/mbm}) structure observed in experiments. Deficiencies of the commonly employed simple one-dimensional "double well" potentials in describing the dynamics of the octahedra are pointed out and discussed.

cond-mat.mtrl-sci↗