Atomistic simulations of magnetic shape memory alloys

Magnetic shape memory (MSM) alloys are novel smart materials which exhibit magnetic field induced strains of up to 10 %. As such they have potential for many technological applications. Also, the strong magneto-structural couplings of the MSM effect make the phenomenon very interesting from a scientific point of view. In this thesis, materials and properties related to the MSM effect are studied with atomistic simulations. Main interest is in the known MSM alloy Ni-Mn-Ga around the Ni2MnGa stoichiometry. One pre-requisite for the MSM effect is the existence of a structural transformation in a magnetic material, and therefore some candidate materials are investigated from this perpective. Here, Ni2MnAl is found to have potential for further studies. The magnetic moment is seen to originate mainly from Mn in the Mn-containing alloys and the existence of different structural phases is ascribed to a band Jahn-Teller effect in the Ni band. This picture is confirmed by comparisons between theoretical and experimental neutron diffraction results. In Ni2MnGa the structural phase transformations are found to be driven by vibrational entropy at finite temperatures. The magnetic key property in the MSM effect is the magnetic anisotropy energy which is studied in Ni2MnGa. The tetragonal structure with c/a = 0.94 is magnetically uniaxial characterized by the first anisotropy constant, but in the presence of several twin variants only the second anisotropy constant may be observed in the measurements. Analysis of the microscopic origins of the magnetic anisotropy shows that Ni has the largest contribution to the magnetic anisotropy energy. Investigations of other structures show that in Ni2MnGa the shortest crystal axis is always the easy axis of magnetization. From other magnetic properties, the Curie temperatures of Ni2MnGa and Ni2MnAl are estimated on the basis of total energy calculations of spin spirals. Ni is found to have an important effect also on the Curie temperatures despite its smaller magnetic moment when compared to Mn. Non-stoichiometric compositions of Ni-Mn-Ga are studied within the rigid band approximation and with supercell calculations. In some cases the rigid band approximation describes the correct trends, but more insight into the alloying effects can be obtained from the supercell calculations. The most important result of these investigations is that in Mn-rich compositions the extra Mn atoms couple antiferromagnetically to the neighbouring Mn atoms. This result implies a decrease of the total magnetic moment with Mn-doping. Also, all the experimentally observed martensite phases are explained theoretically when the extra Mn is explicitly included.reviewe

Time-dependent density-functional theory in the projector augmented-wave method

We present the implementation of the time-dependent density-functional theory both in linear-response and in time-propagation formalisms using the projector augmented-wave method in real-space grids. The two technically very different methods are compared in the linear-response regime where we found perfect agreement in the calculated photoabsorption spectra. We discuss the strengths and weaknesses of the two methods as well as their convergence properties. We demonstrate different applications of the methods by calculating excitation energies and excited state Born–Oppenheimer potential surfaces for a set of atoms and molecules with the linear-response method and by calculating nonlinear emission spectra using the time-propagation method.Peer reviewe

GPAW: open Python package for electronic-structure calculations

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 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 (BSE), 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 of GPU acceleration has been achieved with minor modifications of the GPAW code thanks to the CuPy library. We end the review with an outlook describing some future plans for GPAW

Jättiläismäinen ja kolossaalinen magnetoresistanssi: magneettinen kytkentä Co/Si kerroksissa

Magnetoresistiivisyydellä tarkoitetaan ilmiöitä, joissa aineen sähkönjohtavuus muuttuu ulkoisen magneettikentän vaikutuksesta. Ilmiö on tunnettu jo pitkään, mutta viime vuosina tehdyt havainnot suurista sähkönjohtavuuden muutoksista magneettikentässä, ns. jättiläismäinen ja kolossaalinen magnetoresistanssi, ovat herättäneet kiinnostuksen uudelleen. Tässä työssä on annettu lyhyt katsaus molempiin yllä mainittuihin ilmiöihin. Myös jättiläismäiseen magnetoresistanssiin läheisesti liittyvä oskilloiva kerrosten välinen magneettinen kytkentä on esitelty. Uusista mahdollisista magnetoresistiivisistä rakenteista magneettisten aineiden ja perinteisten elektroniikan materiaalien yhdistäminen on herättänyt kiinnostusta. Tässä työssä on tutkittu kerrosten välistä magneettista kytkentää Co/Si rakenteissa. Kytkentä on laskettu käyttäen tiheysfunktionaaliteoriaa ja kytkennän on havaittu oskilloivan ferromagneettisesta antiferromagneettiseen riippuen piikerroksen paksuudesta. Oskilloinnin jaksoväli on kaksi piikerrosta. Co/Si kerrosten elektronirakenne viittaa kvanttikaivojen muodostumiseen Si kerroksissa. Elektronirakenteen kvalitatiiviset ominaisuudet on selitetty yksinkertaisen kvanttikaivomallin avulla

Optimizing GPAW

GPAW is a versatile software package for first-principles simulations of nanostructures utilizing density-functional theory and time-dependent density-functional theory. Even though GPAW is already used for massively parallel calculations in several supercomputer systems, some performance bottlenecks still exist. First, the implementation based on the Python programming language introduces an I/O bottleneck during initialization which becomes serious when using thousands of CPU cores. Second, the current linear response time-dependent density-functional theory implementation contains a large matrix, which is replicated on all CPUs. When reaching for larger and larger systems, memory runs out due to the replication. In this report, we discuss the work done on resolving these bottlenecks. In addition, we have also worked on optimization aspects that are directed more to the future usage. As the number of cores in multicore CPUs is still increasing, an hybrid parallelization combining shared memory and distributed memory parallelization is becoming appealing. We have experimented with hybrid OpenMP/MPI and report here the initial results. GPAW also performs large dense matrix diagonalizations with the ScaLAPACK library. Due to limitations in ScaLAPACK these diagonalizations are expected to become a bottleneck in the future, which has led us to investigate alternatives for the ScaLAPACK

GPAW - massively parallel electronic structure calculations with Python-based software

AbstractElectronic structure calculations are a widely used tool in materials science and large consumer of supercomputing resources. Traditionally, the software packages for these kind of simulations have been implemented in compiled languages, where Fortran in its different versions has been the most popular choice. While dynamic, interpreted languages, such as Python, can increase the effciency of programmer, they cannot compete directly with the raw performance of compiled languages. However, by using an interpreted language together with a compiled language, it is possible to have most of the productivity enhancing features together with a good numerical performance. We have used this approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix environments, massively parallel supercomputing systems can present some challenges in porting, debugging and profiling the software. In this paper we describe some details of the implementation and discuss the advantages and challenges of the combined Python/C approach. We show that despite the challenges it is possible to obtain good numerical performance and good parallel scalability with Python based software

First-principles calculation of spin spirals in Ni2MnAl and Ni2MnGa

We report here noncollinear magnetic configurations in the Heusler alloys Ni2MnGa and Ni2MnAl which are interesting in the context of the magnetic shape memory effect. The total energies for different spin spirals are calculated and the ground-state magnetic structures are identified. The calculated dispersion curves are used to estimate the Curie temperature which is found to be in good agreement with experiments. In addition, the variation of the magnetic moment as a function of the spiral structure is studied. Most of the variation is associated with Ni, and symmetry constraints relevant for the magnetization are identified. Based on the calculated results, the effect of the constituent atoms in determining the Curie temperature is discussed.Peer reviewe

Birth of the Localized Surface Plasmon Resonance in Monolayer-Protected Gold Nanoclusters

Gold nanoclusters protected by a thiolate monolayer (MPC) are widely studied for their potential applications in site-specific bioconjugate labeling, sensing, drug delivery, and molecular electronics. Several MPCs with 1–2 nm metal cores are currently known to have a well-defined molecular structure, and they serve as an important link between molecularly dispersed gold and colloidal gold to understand the size-dependent electronic and optical properties. Here, we show by using an <i>ab initio</i> method together with atomistic models for experimentally observed thiolate-stabilized gold clusters how collective electronic excitations change when the gold core of the MPC grows from 1.5 to 2.0 nm. A strong localized surface plasmon resonance (LSPR) develops at 540 nm (2.3 eV) in a cluster with a 2.0 nm metal core. The protecting molecular layer enhances the LSPR, while in a smaller cluster with 1.5 nm gold core, the plasmon-like resonance at 540 nm is confined in the metal core by the molecular layer. Our results demonstrate a threshold size for the emergence of LSPR in these systems and help to develop understanding of the effect of the molecular overlayer on plasmonic properties of MPCs enabling engineering of their properties for plasmonic applications