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Heungsoo Kim

Publications and source records attributed to Heungsoo Kim.

3 recordsLinked to original sources

Memristor-Driven Spike Encoding for Fully Implantable Cochlear Implants

Objective: This work aims to demonstrate a low-power, biomimetic auditory sensing concept for fully implantable cochlear implants. The approach draws inspiration from the frequency selectivity and temporal encoding of the cochlea, and uses neuromorphic spike generation to replace conventional signal processing blocks. The goal is to establish a compact, energy-efficient front-end architecture suitable for future implantable systems. Methods: An auditory sensing unit was implemented, consisting of a piezoelectric MEMS cantilever mechanically coupled to a single VO$_2$ nanogap Mott memristor-based oscillator. This configuration enables FFT-free, frequency-selective sensing and direct spike generation, forming a biomimetic auditory front end. The concept was experimentally examined using controlled mechanical excitation. Results: The sensing unit exhibited frequency-selective detection of mechanical vibrations in the nanometer to tens-of-nanometers displacement range and generated biomimetic spiking waveforms. Spike rate-encoding of the input amplitude was demonstrated, with output spiking frequencies tunable between approximately 100 Hz and 1 kHz depending on the excitation level. The waveform was finally converted to a biphasic shape suitable for cochlear implant stimulation. Significance: Temporal encoding is fundamental to natural auditory signal processing in the nervous system. By implementing this principle through neuromorphic spike encoding, the proposed approach can provide significant benefits for cochlear implants. In addition, the circuit has the potential to reduce footprint, energy consumption, and latencies compared with current commercial solutions.

cond-mat.mes-hall

VO$_2$ oscillator circuits optimized for ultrafast, 100 MHz-range operation

Oscillating neural networks are promising candidates for a new computational paradigm, where complex optimization problems are solved by physics itself through the synchronization of coupled oscillating circuits. Nanoscale VO$_2$ Mott memristors are particularly promising building blocks for such oscillating neural networks. Until now, however, not only the maximum frequency of VO$_2$ oscillating neural networks, but also the maximum frequency of individual VO$_2$ oscillators has been severely limited, which has restricted their efficient and energy-saving use. In this paper, we show how the oscillating frequency can be increased by more than an order of magnitude into the 100 MHz range by optimizing the sample layout and circuit layout. In addition, the physical limiting factors of the oscillation frequencies are studied by investigating the switching dynamics. To this end, we investigate how much the set and reset times slow down under oscillator conditions compared to the fastest switching achieved with single dedicated pulses. These results pave the way towards the realization of ultra-fast and energy-efficient VO$_2$-based oscillating neural networks.

cond-mat.mes-hall

Experimental demonstration of superconducting critical temperature increase in electromagnetic metamaterials

A recent proposal that the metamaterial approach to dielectric response engineering may increase the critical temperature of a composite superconductor-dielectric metamaterial has been tested in experiments with compressed mixtures of tin and barium titanate nanoparticles of varying composition. An increase of the critical temperature of the order of 0.15 K compared to bulk tin has been observed for 40% volume fraction of barium titanate nanoparticles. Similar results were also obtained with compressed mixtures of tin and strontium titanate nanoparticles.

physics.optics