Nanoscale analysis of the oxidation state and surface termination of praseodymium oxide ultrathin films on ruthenium(0001)

The complex structure and morphology of ultrathin praseodymia films deposited on a ruthenium(0001) single crystal substrate by reactive molecular beam epitaxy is analyzed by intensity-voltage low-energy electron microscopy in combination with theoretical calculations within an ab initio scattering theory. A rich coexistence of various nanoscale crystalline surface structures is identified for the as-grown samples, notably comprising two distinct oxygen-terminated hexagonal Pr2O3(0001) surface phases as well as a cubic Pr2O3(111) and a fluorite PrO2(111) surface component. Furthermore, scattering theory reveals a striking similarity between the electron reflectivity spectra of praseodymia and ceria due to very efficient screening of the nuclear charge by the extra 4f electron in the former case

Nanometer scale studies of the electrically induced resistive switching of perovskite manganites

Perowskitische Manganoxide sind hochkorrelierte Systeme, die neben einem thermisch induzierten Metall-Isolator-Übergang durch verschiedene Stimuli getriebene Widerstandseffekte zeigen können. Beim Überschreiten kritischer Spannungen oder Ströme treten an Manganaten abrupte Widerstandsänderungen auf. Trotz der großen Aufmerksamkeit, die solche Schalteffekte auch auf Grund ihrer möglichen Nutzbarkeit in nonvolatilen Speicherelementen erfahren, konnte der zugrundeliegende physikalische Mechanismus jedoch bisher nicht vollständig aufgeklärt werden. Diese Arbeit widmet sich dem elektrischen Widerstandsschalten dünner Calcium- und Strontium-dotierter Lanthanmanganatfilme. Dabei wurde atomare Kraftmikroskopie mit leitfähig beschichteten Sonden betrieben, welche neben topographischen Aufzeichnungen auch die Durchführung elektrischer Messungen auf der Nanometerskala erlaubt. Durch Anlegen von Spannungspulsen an die Sondenspitze können leitfähige Regionen an der Manganatoberfläche erzeugt und zerstört werden. Diese leitenden Domänen wurden durch elektrische Messungen charakterisiert und ihre räumliche Gestalt und zeitliche Entwicklung sowie die Abhängigkeit ihres Wachstums von den Pulsparametern untersucht. Als Erklärungsansatz wird ein qualitatives Model eines spannungsinduzierten strukturellen Übergangs eingeführt und alternativen Beschreibungen gegenübergestellt. Ein in Abhängigkeit von der Pulsdauer logarithmisch fortschreitendes Wachstum kann als Kriechprozess verstanden werden und ist somit mit der Vorstellung eines strukturellen Prozesses in Einklang. Darüberhinaus weisen auch der Widerstandsverlauf in Pulsserienexperimenten und die Beobachtung einer zeitlichen Rückbildung metallischer Domänen auf ein Kriecherholungsphänomen hin. Es konnte ferner ein vermutlich lagenweises Widerstandsschalten einer Strontium-dotierten Schicht festgestellt werden, welches ebenfalls im Kontext einer strukturellen Umwandlung als Ursache der Widerstandsänderung verständlich erscheint

Visible range colossal magnetorefractive effect in (La 1 − y Pr y ) 2/3 Ca 1/3 MnO 3 films

We report a colossal magnetorefractive effect (MRE) in epitaxial thin films of a classical colossal magnetoresistance (CMR) manganite, (La1 − yPry)2/3Ca1/3MnO3 (y = 0.375 and 0.7). Close to the ferromagnetic (FM) phase transition a moderate applied magnetic field, H∼10 kOe, results in a reduction of the optical reflectance by ∼18% for the photon energy E∼2.7 eV. The MRE spectral behavior with three pronounced maxima at E = 1.6, 2.7 and 4.0eV points out an inter-site nature of the involved optical transitions. The results are discussed within a phase separation scenario with coexisting FM metallic nanodomains antiferromagnetically coupled by correlated polarons. The probability of MRE optical transitions is maximal for antiparallel alignment of Mn3+/Mn4+-spins realized for the coercive field, Hc∼200–800 Oe, and is suppressed by stronger fields, which favor FM metallic behavior. As a result, both the optical reflectivity and the electrical resistance decrease, yielding a close similarity between the CMR and MRE behavior.Open Access Publikationsfonds 2014peerReviewe

Low-energy electron microscopy intensity-voltage data -- factorization, sparse sampling, and classification

Low-energy electron microscopy (LEEM) taken as intensity-voltage (I-V) curves provides hyperspectral images of surfaces, which can be used to identify the surface type, but are difficult to analyze. Here, we demonstrate the use of an algorithm for factorizing the data into spectra and concentrations of characteristic components (FSC3) for identifying distinct physical surface phases. Importantly, FSC3 is an unsupervised and fast algorithm. As example data we use experiments on the growth of praseodymium oxide or ruthenium oxide on ruthenium single crystal substrates, both featuring a complex distribution of coexisting surface components, varying in both chemical composition and crystallographic structure. With the factorization result a sparse sampling method is demonstrated, reducing the measurement time by 1-2 orders of magnitude, relevant for dynamic surface studies. The FSC3 concentrations are providing the features for a support vector machine (SVM) based supervised classification of the types. Here, specific surface regions which have been identified structurally, via their diffraction pattern, as well as chemically by complementary spectro-microscopic techniques, are used as training sets. A reliable classification is demonstrated on both exemplary LEEM I-V datasets.Comment: 13 pages, 7 figure

Low-energy electron microscopy intensity-voltage data – factorization, sparse sampling, and classification

Low-energy electron microscopy (LEEM) taken as intensity-voltage (I-V) curves provides hyperspectral images of surfaces, which can be used to identify the surface type, but are difficult to analyze. Here, we demonstrate the use of an algorithm for factorizing the data into spectra and concentrations of characteristic components () for identifying distinct physical surface phases. Importantly, is an unsupervised and fast algorithm. As example data we use experiments on the growth of praseodymium oxide or ruthenium oxide on ruthenium single crystal substrates, both featuring a complex distribution of coexisting surface components, varying in both chemical composition and crystallographic structure. With the factorization result a sparse sampling method is demonstrated, reducing the measurement time by 1-2 orders of magnitude, relevant for dynamic surface studies. The concentrations are providing the features for a support vector machine (SVM) based supervised classification of the surface types. Here, specific surface regions which have been identified structurally, via their diffraction pattern, as well as chemically by complementary spectro-microscopic techniques, are used as training sets. A reliable classification is demonstrated on both exemplary LEEM I-V datasets