Evidence map›Paper›PMID 36646505›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023

In-Memory-Computed Low-Frequency Noise Spectroscopy for Selective Gas Detection Using a Reducible Metal Oxide.

Wonjun Shin, Jaehyeon Kim, Gyuweon Jung, Suyeon Ju, Sung-Ho Park, Yujeong Jeong, Seongbin Hong, Ryun-Han Koo, Yeongheon Yang, Jae-Joon Kim and 2 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Low-Frequency Noise Spectroscopy for Navigating Geometrically Varying Strain Effects in HfOAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Wonjun ShinDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.ORCID https://orcid.org/0000-0001-9122-2458
Jaehyeon KimDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Gyuweon JungDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Suyeon JuDepartment of Materials Science and Engineering and Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea.
Sung-Ho ParkDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Yujeong JeongDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Seongbin HongDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Ryun-Han KooDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Yeongheon YangResearch and Development Division, SK Hynix Inc., Icheon, 17736, Republic of Korea.
Jae-Joon KimDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.
Seungwu HanDepartment of Materials Science and Engineering and Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea.
Jong-Ho LeeDepartment of Electrical and Computer Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea.ORCID https://orcid.org/0000-0003-3559-9802

Funding

Education and Research Program for Future ICT PioneersInstitute of Information & communications Technology Planning & EvaluationKorea government (MSIT) 2021001776Ministry of Science and ICT 2021M3F3A2A02037889National Research Foundation of KoreaSeoul National UniversitySK Hynix Inc.
6 · The paper itself

Abstract

Concerns about indoor and outdoor air quality, industrial gas leaks, and medical diagnostics are driving the demand for high-performance gas sensors. Owing to their structural variety and large surface area, reducible metal oxides hold great promise for constructing a gas-sensing system. While many earlier reports have successfully obtained a sufficient response to various types of target gases, the selective detection of target gases remains challenging. In this work, a novel method, low-frequency noise (LFN) spectroscopy is presented, to achieve selective detection using a single FET-type gas sensor. The LFN of the sensor is accurately modeled by considering the charge fluctuation in both the sensing material and the FET channel. Exposure to different target gases produces distinct corner frequencies of the power spectral density that can be used to achieve selective detection. In addition, a 3D vertical-NAND flash array is used with the fast Fourier transform method via in-memory-computing, significantly improving the area and power efficiency rate. The proposed system provides a novel and efficient method capable of selectively detecting a target gas using in-memory-computed LFN spectroscopy and thus paving the way for the further development in gas sensing systems.

Indexed as

in-memory-computinglow-frequency noise (LFN)selective detectiontungsten oxide

Identifiers

PMID36646505
PMCPMC9982552

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.