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Zaluzhnyy, Ivan A.

Publications and source records attributed to Zaluzhnyy, Ivan A..

Structural Changes in YBa 2 Cu 3 O 7 Thin Films Modified with He + -Focused Ion Beam for High-Temperature Superconductive Nanoelectronics

Irradiation of high-temperature superconductor YBa 2 Cu 3 O 7 (YBCO) with high-energy He + ions is known to cause structural changes in the YBCO film, decreasing the critical temperature T C and finally leading to a superconductor-to-insulator transition. Here, this allows one to pattern narrow insulating regions with a focused ion beam (FIB) and thus fabricate nanoscale Josephson junctions on YBCO films. Moreover, such ion irradiation is known to cause structural changes in the YBCO film. However, details of how these structural changes occur in nanoscale devices produced by FIB remain unknown. Using nanofocus X-ray diffraction, we study the changes in the YBCO crystal lattice and investigate how the nature of these changes depends on the size of the irradiated regions. These data provide an important understanding of how oxide superconductors can be tailored at the nanometer scale for various applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring fingerprints of ultrafast structural dynamics in molecular solutions with an X-ray laser

We apply ultrashort x-ray laser pulses to track optically excited structural dynamics of [Ir 2 (dimen) 4 ] 2+ molecules in solution. In our exploratory study we determine angular correlations in the scattered x-rays, which comprise a complex fingerprint of the ultrafast dynamics. Model-assisted analysis of the experimental correlation data allows us to elucidate various aspects of the photoinduced changes in the excited molecular ensembles. We unambiguously identify that in our experiment the photoinduced transition dipole moments in [Ir 2 (dimen) 4 ] 2+ molecules are oriented perpendicular to the Ir-Ir bond. The analysis also shows that the ground state conformer of [Ir 2 (dimen) 4 ] 2+ with a larger Ir–Ir distance is mostly responsible for the formation of the excited state. We also reveal that the ensemble of solute molecules can be characterized with a substantial structural heterogeneity due to solvent influence. In conclusion, the proposed x-ray correlation approach offers an alternative path for studies of ultrafast structural dynamics of molecular ensembles in the liquid and gas phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proton distribution visualization in perovskite nickelate devices utilizing nanofocused x rays

We use a 30-nm x-ray beam to study the spatially resolved properties of a SmNiO 3 -based nanodevice that is doped with protons. The x-ray absorption spectra supported by density-functional theory simulations show partial reduction of nickel valence in the region with high proton concentration, which leads to the insulating behavior. Concurrently, x-ray diffraction reveals only a small lattice distortion in the doped regions. Together, our results directly show that the knob which proton doping modifies is the electronic valency and not the crystal lattice. Overall, the studies are relevant to ongoing efforts to disentangle structural and electronic effects across metal-insulator phase transitions in correlated oxides.

36 MATERIALS SCIENCE↗

Low-temperature emergent neuromorphic networks with correlated oxide devices

Significance Designing neuromorphic hardware for cryoelectronics is an important area of research as the field of computing paradigms beyond complementary metal-oxide-semiconductor (CMOS) progresses. Superconductivity and metal−insulator transitions are two of the most celebrated emergent, collective properties found in quantum materials such as strongly correlated oxides. Here, we present simulations of artificial neural networks that can be designed by combining superconducting devices (e.g. Josephson junctions) with Mott metal−insulator transition−based tunable resistor devices. Our simulations show that 1) neurons and synapses can be seamlessly created, 2) their functions can be tuned via learning, and 3) controlling disorder by incorporating light ions enables exponential multiplicity of states. The results open up directions for incorporating emergent behavior seen in condensed matter into hardware design for artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

Perovskite neural trees

Trees are used by animals, humans and machines to classify information and make decisions. Natural tree structures displayed by synapses of the brain involves potentiation and depression capable of branching and is essential for survival and learning. Demonstration of such features in synthetic matter is challenging due to the need to host a complex energy landscape capable of learning, memory and electrical interrogation. We report experimental realization of tree-like conductance states at room temperature in strongly correlated perovskite nickelates by modulating proton distribution under high speed electric pulses. This demonstration represents physical realization of ultrametric trees, a concept from number theory applied to the study of spin glasses in physics that inspired early neural network theory dating almost forty years ago. We apply the tree-like memory features in spiking neural networks to demonstrate high fidelity object recognition, and in future can open new directions for neuromorphic computing and artificial intelligence.

36 MATERIALS SCIENCE↗