Jongyup Lim

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Lim

First Name

Jongyup

ORCID

0000-0003-0306-3966

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Publications1 - 9 of 9

An Adiabatic Sense and Set Rectifier for Improved Maximum-Power-Point Tracking in Piezoelectric Harvesting with 541% Energy Extraction Gain
Peng, Yimai; Choo, David Kyojin; Oh, Sechang; et al. (2019)
2019 IEEE International Solid-State Circuits Conference (ISSCC)
Piezoelectric energy harvesters (PEHs) convert mechanical energy from vibrations into electrical energy. They have become popular in energy-autonomous IoT systems. However, the total energy extracted by a PEH is highly sensitive to matching between the PEH impedance and the energy extraction circuit. Prior solutions include the use of a full-bridge rectifier (FBR) and a so-called synchronous electric-charge extraction (SECE) [1], and are suitable for non-periodic vibrations. However, their extraction efficiency is low since the large internal capacitance C p (usually 10's of nF) of the PEH (Fig. 27.2.1) prevents the output voltage from reaching its maximum power point (MPP) under a typical sinusoidal and transient excitation (V MPP = 1/2·I p R p ). A recently proposed technique [2,3,4], called bias-flip, achieves a higher extraction efficiency by forcing a predetermined constant voltage at the PEH output, V p , which is then flipped every half-period of the assumed sinusoidal excitation (Fig. 27.2.1, top left). To flip V p , the energy in capacitor C p is extracted using either a large external inductor [2,3] or capacitor arrays [4]. It is then restored with the opposite polarity (Fig. 27.2.1, top). However, V MPP of the PEH varies with sinusoidal current I p ; hence, the two fixed values of V p in the flip-bias technique either over or underestimate V MPP for much of the oscillation cycle (pattern filled regions in Fig. 27.2.1, top right). In addition, none of the prior approaches compensate for V MPP -waveform amplitude changes, due to input intensity variations or decaying oscillations after an impulse, further degrading efficiency.
A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry
Lim, Jongyup; Lee, Jungho; Moon, Eunseong; et al. (2022)
IEEE Journal of Solid-State Circuits
Miniaturized and wireless near-infrared (NIR)-based neural recorders with optical powering and data telemetry have been introduced as a promising approach for safe long-term monitoring with the smallest physical dimension among state-of-the-art standalone recorders. However, the main challenge for the NIR-based neural recording integrated circuits (ICs) is to maintain robust operation in the presence of light-induced parasitic short-circuit current from junction diodes. This is especially true when the signal currents are kept small to reduce power consumption. In this work, we present a light-tolerant and low-power neural recording IC for motor prediction that can fully function in up to 300 μW/mm² of light exposure. It achieves the best-in-class power consumption of 0.57 μW at 38 °C with a 4.1 noise efficiency factor (NEF) pseudo-resistor-less amplifier, an on-chip neural feature extractor, and individual mote-level gain control. Applying the 20-channel pre-recorded neural signals of a monkey, the IC predicts finger position and velocity with a correlation coefficient up to 0.870 and 0.569, respectively, with individual mote-level gain control enabled. In addition, wireless measurement is demonstrated through optical power and data telemetry using a custom photovoltaic (PV)/light-emitting diode (LED) GaAs chip wire bonded to the proposed IC.
A Sub-mm³ Wireless Neural Stimulator IC for Visual Cortical Prosthesis With Optical Power Harvesting and 7.5-kb/s Data Telemetry
Lee, Jungho; Letner, Joseph G.; Lim, Jongyup; et al. (2024)
IEEE Journal of Solid-State Circuits
This article proposes StiMote, an untethered, free-floating and individually addressable stimulator mote designed for visual cortex stimulation, aimed at vision restoration. The system is optically powered by a custom photovoltaic (PV) layer. In addition, the photodiode (PD) layer captures the light modulation and forwards it to the optical receiver (ORX) including a tranimpedance amplifier. Translated instructions can assign a unique slot, up to 1024 available, to each mote within the time-division multiple access (TDMA) framework. In this work, we propose an automatic charge balance (CB) technique that monitors the injected charge to balance in bi-phasic switched-capacitor stimulation (SCS). The chip was confirmed fully functional when operated completely wirelessly using harvested light. Measurement results revealed a power consumption of 4.48 μ W with a 7.5-kb/s optical downlink data rate, corresponding to continuous updates at 2.5 Hz of 1024 motes to their individual 3-b stimulation intensity levels. The dc–dc converter, responsible for providing high voltage for stimulation, demonstrated 4.3-V output voltage when unloaded, with a maximum efficiency of 67.4%. The proposed CB circuit exhibited linear controllability of stimulation charge up to 16 nC, with a charge imbalance of less than 0.2 nC. Furthermore, in vitro testing confirmed the absence of chemical reactions at electrodes, and in vivo experiments conducted on live rats verified the effectiveness of the stimulation through StiMote.
A 260×274 μm2 572 nW Neural Recording Micromote Using Near-Infrared Power Transfer and an RF Data Uplink
Atzeni, Gabriele; Lim, Jongyup; Liao, Jiawei; et al. (2022)
2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
This paper presents an optically powered neural recording system for motor prediction using distributed free-floating motes. The proposed mote includes a neural recording amplifier, a data converter, feature extraction, and an on-chip antenna for implementing an RF uplink consuming only 42 nW. The entire mote IC dissipates 572 nW and occupies an area of 260×274 μm 2 , representing the smallest neural recording system with RF uplink to date. Wireless and concurrent communication with multiple units is also demonstrated based on the code-division multiplexing.
An Efficient Piezoelectric Energy Harvesting Interface Circuit Using a Sense-and-Set Rectifier
Peng, Yimai; Choo, Kyojin D.; Oh, Sechang; et al. (2019)
IEEE Journal of Solid-State Circuits
A 510-pW 32-kHz Crystal Oscillator With High Energy-to-Noise-Ratio Pulse Injection
Xu, Li; Jang, Taekwang; Lim, Jongyup; et al. (2022)
IEEE Journal of Solid-State Circuits
This article introduces a 32-kHz crystal oscillator (XO) with high energy-to-noise-ratio pulse injection at subharmonic frequency. A T/4-delay clock slicer is proposed to convert the sinusoidal crystal waveform into an output clock of 32 kHz and to introduce a delay of T/4, providing proper timing for energy injections. The output clock feeds frequency dividers and generates pulses to activate the proposed all-NMOS differential driver at 4 kHz. It enables two injections in eight periods at the peak and valley of the crystal oscillation, with the crystal running freely between injections. This configuration achieves a 2-ppb Allan deviation floor. The less frequent injections reduce the injection overhead, enabling the lowest reported power consumption of published nW XOs (0.51 nW). At 0.45 V, the proposed XO operates across a temperature range of -25 °C to 125 °C, the widest reported range for nW XOs. This design is fabricated in the 40-nm CMOS and occupies 0.02 mm².
A Wireless Neural Stimulator IC for Cortical Visual Prosthesis
Lee, Jungho; Letner, Joseph; Lim, Jongyup; et al. (2023)
2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
We propose a 0.25 x 0.25 x 0.3 mm (∼0.02 mm 3 ) optically powered mote for visual cortex stimulation to restore vision. Up to 1024 implanted motes can be individually addressed. The complete StiMote system was confirmed fully functional when optically powered and cortex stimulation was confirmed in-vivo with a live rat brain.
Bridging the “Last Millimeter” Gap of Brain-Machine Interfaces via Near-Infrared Wireless Power Transfer and Data Communications
Moon, Eunseong; Barrow, Michael; Lim, Jongyup; et al. (2021)
ACS Photonics
Arrays of floating neural sensors with a high channel count that covers an area of square centimeters and larger would be transformative for neural engineering and brain–machine interfaces. Meeting the power and wireless data communications requirements within the size constraints for each neural sensor has been elusive due to the need to incorporate sensing, computing, communications, and power functionality in a package of approximately 100 μm on a side. In this work, we demonstrate a near-infrared optical power and data communication link for a neural recording system that satisfies size requirements to achieve dense arrays and power requirements to prevent tissue heating. The optical link is demonstrated using an integrated optoelectronic device consisting of a tandem photovoltaic cell and microscale light-emitting diode. End-to-end functionality of a wireless neural link within system constraints is demonstrated using a prerecorded neural signal between a self-powered CMOS integrated circuit and single photon avalanche photodiode.
A Noise-Efficient Neural Recording Amplifier Using Discrete-Time Parametric Amplification
Jang, Taekwang; Lim, Jongyup; Choo, Kyojin; et al. (2018)
IEEE Solid-State Circuits Letters

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Jongyup Lim

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