Published Version

This study supports the expansion of the successful aging model by incorporating ICT access and use. Further, it assists in the identification of specific technologies that promote active engagement in later life for women and men.

We report the influence of random point defects introduced by 3 MeV proton irradiation (doses of 0.5×10 16 , 1×10 16 , 2×10 16 and 6×10 16 cm −2 ) on the vortex dynamics of co-evaporated 1.3 μm thick, GdBa 2 Cu 3 O 7−δ coated conductors. Our results indicate that the inclusion of additional random point defects reduces the low field and enhances the in-field critical current densities J c . The main in-field J c enhancement takes place below 40 K, which is in agreement with the expectations for pinning by random point defects. In addition, our data show a slight though clear increase in flux creep rates as a function of irradiation fluence. Maley analysis indicates that this increment can be associated with a reduction in the exponent μ characterizing the glassy behavior.

Ohm's law is a fundamental paradigm in the electrical transport of metals. Any transport signatures violating Ohm's law would give an indisputable fingerprint for a novel metallic state. Here, we uncover the breakdown of Ohm's law owing to a topological structure of the chiral anomaly in the Weyl metal phase. We observe nonlinear I-V characteristics in BiSb single crystals in the diffusive limit, which occurs only for a magnetic-field-aligned electric field (E∥B). The Boltzmann transport theory with the charge pumping effect reveals the topological-in-origin nonlinear conductivity, and it leads to a universal scaling function of the longitudinal magnetoconductivity, which completely describes our experimental results. As a hallmark of Weyl metals, the nonlinear conductivity provides a venue for nonlinear electronics, optical applications, and the development of a topological Fermi-liquid theory beyond the Landau Fermi-liquid theory.

We investigate the effect of heavy ion irradiation (1.4 GeV Pb) on the vortex matter in Ba (Fe 0.92 Co 0.08 ) 2 As 2 single crystals by superconducting quantum interference device (SQUID) magnetometry. The defects created by the irradiation are discontinuous amorphous tracks, resulting in an effective track density smaller than 25% of the nominal doses. We observe large increases in the critical current density (J c ), ranging from a factor of ∼3 at low magnetic fields to a factor of ∼10 at fields close to 1 T after irradiation with a nominal fluence of B Φ = 3.5 T. From the normalized flux creep rates (S) and the Maley analysis, we determine that the J c increase can be mainly attributed to a large increment in the pinning energy, from <50 K to ≈500 K, while the glassy exponent μ changes from ∼1.5 to <1. Although the enhancement of J c is substantial in the entire temperature range and S is strongly suppressed, the artificial pinning landscape induced by the irradiation does not modify significantly the crossover to fast creep in the field-temperature vortex phase diagram.

The complete hardware implementation of an optoelectronic neuromorphic computing system is considered as one of the most promising solutions to realize energy‐efficient artificial intelligence. Here, a fully light‐driven and scalable optoelectronic neuromorphic circuit with metal‐chalcogenide/metal‐oxide heterostructure phototransistor and photovoltaic divider is proposed. To achieve wavelength‐selective neural operation and hardware‐based pattern recognition, multispectral light modulated bidirectional synaptic circuits are utilized as an individual pixel for highly accurate and large‐area neuromorphic computing system. The wavelength selective control of photo‐generated charges at the heterostructure interface enables the bidirectional synaptic modulation behaviors including the excitatory and inhibitory modulations. More importantly, a 7 × 7 neuromorphic pixel circuit array is demonstrated to show the viability of implementing highly accurate hardware‐based pattern training. In both the pixel training and pattern recognition simulation, the neuromorphic circuit array with the bidirectional synaptic modulation exhibits lower training errors and higher recognition rates, respectively.

Diverse artificial synapse structures and materials are widely proposed for neuromorphic hardware systems beyond von Neumann architecture owing to their capability to mimic complex information processing tasks such as image recognition, natural language processing, and learning. Nevertheless, temporal and spatial randomness in the movement of ion and electron particles that exist in materials usually prevents the solid‐state‐based synaptic devices from enabling the reliable modulation of synaptic plasticity. An aluminum nanoparticle (Al NP)‐embedded indium gallium zinc oxide (IGZO) synaptic transistor whose spike peak level and conductance change can be precisely modulated by the density of Al NPs within the IGZO channel is demonstrated. Essential synaptic functions including excitatory or inhibitory postsynaptic current, paired pulse facilitation, and short‐term potentiation or depression are also thoroughly emulated in the synaptic transistor device with the most optimized Al NP density: IGZO:Al NPs (6 nm). Moreover, controllable switching from short‐term to long‐term memory regimes essential for a learning task is demonstrated. Simulation results prove that this transistor can provide a decent recognition accuracy for neuromorphic computing. Indeed, the integrated IGZO:Al NP synaptic circuit with the effective synaptic plasticity will facilitate the implementation of a reconfigurable neuromorphic computing system.

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