Sami Kaappa

Defects, impurities, and embedded particles in ferromagnetic materials are long known to be responsible for the Barkhausen effect due to the jerky field-driven motion of domain walls and have more recently been shown to play a role also in domain wall dynamics in nanoscale ferromagnetic structures used in spintronics devices. Simulating the magnetic domain wall dynamics in the micromagnetic framework offers a straightforward route to study such systems and phenomena. However, the related work in the past suffers from material imperfections being introduced without proper physical foundation. Here, we implement dislocation stress fields in micromagnetic simulations through the induced anisotropy fields by inverse magnetostriction. The effects of individual dislocations on domain wall dynamics in thin films of different Fe surface lattice planes are characterized numerically. As a demonstration of the applicability of the implementation, we consider disorder fields due to randomly positioned dislocations with different densities, and study the avalanche-like transient approach towards the depinning transition of a domain wall driven by a slowly increasing external magnetic field.

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

We introduce a computational method for global optimization of structure and ordering in atomic systems. The method relies on interpolation between chemical elements, which is incorporated in a machine-learning structural fingerprint. The method is based on Bayesian optimization with Gaussian processes and is applied to the global optimization of Au-Cu bulk systems, Cu-Ni surfaces with CO adsorption, and Cu-Ni clusters. The method consistently identifies low-energy structures, which are likely to be the global minima of the energy. For the investigated systems with 23–66 atoms, the number of required energy and force calculations is in the range 3–75.

Local optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between the molecule and the substrate. In this work, we show how the explicit modeling of different characteristics of the bonds in these systems improves the performance of machine learning methods for optimization. We introduce an anisotropic kernel in the Gaussian process regression framework that guides the search for the local minimum, and we show its overall good performance across different types of atomic systems. The method shows a speed-up of up to a factor of two compared with the fastest standard optimization methods on adsorption systems. Additionally, we show that a limited memory approach is not only beneficial in terms of overall computational resources but can also result in a further reduction of energy and force calculations.

Surface organic ligands play a critical role in stabilizing atomically precise metal nanoclusters in solutions. However, it is still challenging to prepare highly robust ligated metal nanoclusters that are surface‐active for liquid‐phase catalysis without any pre‐treatment. Now, an N‐heterocyclic carbene‐stabilized Au₂₅ nanocluster with high thermal and air stabilities is presented as a homogenous catalyst for cycloisomerization of alkynyl amines to indoles. The nanocluster, characterized as [Au₂₅(ⁱPr₂‐bimy)₁₀Br₇]²⁺ (ⁱPr₂‐bimy=1,3‐diisopropylbenzimidazolin‐2‐ylidene) (1), was synthesized by direct reduction of AuSMe₂Cl and ⁱPr₂‐bimyAuBr with NaBH₄ in one pot. X‐ray crystallization analysis revealed that the cluster comprises two centered Au₁₃ icosahedra sharing a vertex. Cluster 1 is highly stable and can survive in solution at 80 °C for 12 h, which is superior to Au₂₅ nanoclusters passivated with phosphines or thiols. DFT computations reveal the origins of both electronic and thermal stability of 1 and point to the probable catalytic sites. This work provides new insights into the bonding capability of N‐heterocyclic carbene to Au in a cluster, and offers an opportunity to probe the catalytic mechanism at the atomic level.

Gold superatom nanoclusters stabilized entirely by N-heterocyclic carbenes (NHCs) are reported. The reduction of well-defined NHC–Au–Cl complexes produces clusters com-prised of an icosahedral Au13 core surrounded by a symmetrical arrangement of 9 NHCs and 3 chlorides. X-ray crystallography shows that the clusters are characterized by multiple CH–π and π–π interactions, which rigidify the ligand and likely con-tribute to the exceptionally high photoluminescent quantum yields observed, up to 16.0 %, which is significantly greater than the most luminescent ligand-protected Au13 superatom cluster. Density functional theory analysis suggests that clus-ters are 8-electron superatoms with a wide HOMO-LUMO energy gap of 2 eV. Consistent with this, the clusters have high stability relative to all-phosphine clusters.