JeongWoo Jeon

All Publications

• Atomic LayerDeposition of High-Density GeSe Filmsfor Stable Vertical Ovonic Threshold Switching and Selector-Only Memory CHEMISTRY OF MATERIALS Kim, S., Jeon, J., Park, B., Choi, W., Jeon, G., Jeon, S., Park, J., Kim, W., Lim, J., Ahn, D., Yoo, C., Hwang, C. 2026

  View details for DOI 10.1021/acs.chemmater.6c01199

  View details for Web of Science ID 001826861800001

• Neuromorphic olfaction with ultralow-power gas sensors and ovonic threshold switch SCIENCE ADVANCES Kang, M., Han, J., Lee, K., Jeong, J., Yoo, C., Jeon, J., Park, B., Choi, W., Ahn, J., Yoon, K., Hwang, C., Park, I. 2025; 11 (39): eadv9222

  Abstract

  With increasing demand for gas sensors in mobile devices, research on developing an electronic nose (E-nose) is actively conducted. However, conventional E-nose systems based on von Neumann computing have encountered challenges such as high hardware costs and power consumption because of the necessity of hardware-intensive circuits and processors. This work implements low-power artificial olfactory neuron modules within a spiking neural network (SNN) to address this issue. The artificial olfactory neuron module is developed by connecting a GeSe-based ovonic threshold switch and a micro-light-emitting diode (μLED) platform-based semiconductor metal oxide gas sensor in series. The use of μLED gas sensors enables ultralow-power operation, resulting in substantially decreased power consumption. The artificial olfactory neuron module generates spike signals with low operation voltage, demonstrating energy efficiency and advanced performance. A real-time gas classification based on the SNN is feasibly conducted with an accuracy of 99.6%. Moreover, it is possible to classify different ingredients under humidity disturbance conditions through a hardware SNN.

  View details for DOI 10.1126/sciadv.adv9222

  View details for Web of Science ID 001579007200018

  View details for PubMedID 40991689

  View details for PubMedCentralID PMC12459429

• Defect Formation and Electrical Transformation in SiO₂ Thin Films via Ti-Induced Interdiffusion ACTA MATERIALIA Yoon, S., Jeon, J., Lee, J., Park, J., Lee, C., Yu, K., Bae, H., Kim, K., Heo, K., Hwang, C., Cho, D., Lee, T., Lee, Y. 2025; 296

  View details for DOI 10.1016/j.actamat.2025.121313

  View details for Web of Science ID 001536970600001

• Low-temperature atomic layer deposition of metastable MnTe films for phase change memory devices JOURNAL OF MATERIALS CHEMISTRY C Jeon, G., Jeon, J., Kim, W., Kim, D., Noh, W., Choi, W., Park, B., Jeon, S., Kim, S., Yoo, C., Hwang, C. 2025

  View details for DOI 10.1039/d4tc05499g

  View details for Web of Science ID 001431486600001

• Atomic layer deposition of Sn-doped germanium diselenide for an As-free Ovonic threshold switch with low off-current DALTON TRANSACTIONS Park, B., Jeon, J., Kim, W., Choi, W., Jeon, G., Jeon, S., Kim, S., Yoo, C., Lim, J., Sung, Y., Ahn, D., Hwang, C. 2024

  Abstract

  This work introduces the atomic layer deposition (ALD) of Sn-doped GeSe2 (SnGS2) films for developing arsenic-free Ovonic threshold switch (OTS) devices with low off-current (Ioff) and desirable threshold voltage (Vt). The undoped GeSe2 film exhibits high Vt and low endurance characteristics despite its low Ioff originating from a large mobility gap. Such problems could be overcome by appropriate doping, and thus, Sn was doped into the GeSe2 film using a supercycle consisting of SnNx and GeSe2 subcycles. The co-injection of NH3 with Se-precursor ([(CH3)3Si]2Se) during the GeSe2 subcycle generated a reactive H2Se intermediate, which enhanced the reactivity and transformed the pre-deposited SnNx to SnSe2. The overall cation-to-anion ratio of the deposited films remained at approximately 1 : 2, with amorphous structure and smooth surface morphology. The planar OTS device using SnGS2 films with a Sn concentration of 9.6%, for which the crystallization temperature was >400 °C, showed the lowest Vt of ∼3.5 V and Ioff of ∼12.5 nA at half Vt and demonstrated switching endurance over 106 cycles. Furthermore, a vertical-type OTS device was fabricated using the same SnGS2 film using the excellent step coverage of ALD, exhibiting similar switching characteristics to its planar counterpart.

  View details for DOI 10.1039/d4dt02946a

  View details for Web of Science ID 001373311000001

  View details for PubMedID 39651556

• Reversible modulation of critical electric fields for a field-induced ferroelectric effect with field-cycling in ZrO₂ thin films JOURNAL OF MATERIALS CHEMISTRY C Shin, J., Shin, D., Kim, K., Seo, H., Ye, K., Jeon, J., Kim, T., Paik, H., Song, H., Lee, S., Choi, J., Hwang, C. 2024; 12 (38)

  View details for DOI 10.1039/d4tc03024a

  View details for Web of Science ID 001312711000001

• Vertically Stackable Ovonic Threshold Switch Oscillator Using Atomic Layer Deposited Ge0.6Se0.4 Film for High-Density Artificial Neural Networks. ACS applied materials & interfaces Jeon, J. W., Park, B., Jang, Y. H., Lee, S. H., Jeon, S., Han, J., Ryoo, S. K., Kim, K. D., Shim, S. K., Cheong, S., Choi, W., Jeon, G., Kim, S., Yoo, C., Han, J. K., Hwang, C. S. 2024

  Abstract

  Nanodevice oscillators (nano-oscillators) have received considerable attention to implement in neuromorphic computing as hardware because they can significantly improve the device integration density and energy efficiency compared to complementary metal oxide semiconductor circuit-based oscillators. This work demonstrates vertically stackable nano-oscillators using an ovonic threshold switch (OTS) for high-density neuromorphic hardware. A vertically stackable Ge0.6Se0.4 OTS-oscillator (VOTS-OSC) is fabricated with a vertical crossbar array structure by growing Ge0.6Se0.4 film conformally on a contact hole structure using atomic layer deposition. The VOTS-OSC can be vertically integrated onto peripheral circuits without causing thermal damage because the fabrication temperature is <400 °C. The fabricated device exhibits oscillation characteristics, which can serve as leaky integrate-and-fire neurons in spiking neural networks (SNNs) and coupled oscillators in oscillatory neural networks (ONNs). For practical applications, pattern recognition and vertex coloring are demonstrated with SNNs and ONNs, respectively, using semiempirical simulations. This structure increases the oscillator integration density significantly, enabling complex tasks with a large number of oscillators. Moreover, it can enhance the computational speed of neural networks due to its rapid switching speed.

  View details for DOI 10.1021/acsami.3c18625

  View details for PubMedID 38491936

• A Review of Advances in Deposition Methods and Material Properties of Superlattice Phase-Change Memory ACS APPLIED ELECTRONIC MATERIALS Yoo, C., Jeon, J., Park, B., Choi, W., Jeon, G., Jeon, S., Kim, S., Hwang, C. 2023; 5 (11): 5794-5808

  View details for DOI 10.1021/acsaelm.3c01022

  View details for Web of Science ID 001110615700001

• Enhanced pseudo-atomic layer deposition of antimony telluride thin films by co-injecting NH3 gas with both precursors JOURNAL OF MATERIALS CHEMISTRY C Jeon, S., Jeon, J., Choi, W., Park, B., Jeon, G., Yoo, C., Hwang, C. 2023

  View details for DOI 10.1039/d3tc00007a

  View details for Web of Science ID 000935130400001