Artificial visual perception neural system using a solution-processable MoS<sub>2</sub>-based in-memory light sensor

Dayanand Kumar; Lana Joharji; Hanrui Li; Ayman Rezk; Ammar Nayfeh; Nazek El-Atab

doi:10.1038/s41377-023-01166-7

Go to Nature Website

Your Location：

Home >

Browse articles >

Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor

Original Articles

- Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor
- Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor
- LSA 2023年12卷第8期页码：1583-1594
- Affiliations：
  
  1.Smart, Advanced Memory Devices and Applications (SAMA) Laboratory, Electrical and Computer Engineering Program, Computer Electrical Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Kingdom of Saudi Arabia
  2.Department of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi 127788, United Arab Emirates
- Author bio：
  
  Nazek El-Atab (nazek.elatab@kaust.edu.sa)
- Funds：
- DOI：10.1038/s41377-023-01166-7
  中图分类号：
- 纸质出版日期：2023-08-31，
  
  网络出版日期：2023-05-05，
  
  收稿日期：2022-11-22，
  
  修回日期：2023-04-08，
  
  录用日期：2023-04-19
- Accepted：
Scan QR Code
Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor[J]. LSA, 2023,12(8):1583-1594.

Kumar, D. et al. Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor. Light: Science & Applications, 12, 1583-1594 (2023).
Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor[J]. LSA, 2023,12(8):1583-1594. DOI： 10.1038/s41377-023-01166-7.

Kumar, D. et al. Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor. Light: Science & Applications, 12, 1583-1594 (2023). DOI： 10.1038/s41377-023-01166-7.

摘要

Abstract

Optoelectronic devices are advantageous in in-memory light sensing for visual information processing

recognition

and storage in an energy-efficient manner. Recently

in-memory light sensors have been proposed to improve the energy

area

and time efficiencies of neuromorphic computing systems. This study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS

metal–oxide–semiconductor (MOS) charge-trapping memory structure—the basic structure for charge-coupled devices (CCD)—and showing its suitability for in-memory light sensing and artificial visual perception. The memory window of the device increased from 2.8 V to more than 6 V when the device was irradiated with optical lights of different wavelengths during the program operation. Furthermore

the charge retention capability of the device at a high temperature (100 ℃) was enhanced from 36 to 64% when exposed to a light wavelength of 400 nm. The larger shift in the threshold voltage with an increasing operating voltage

confirmed that more charges were trapped at the Al

/MoS

interface and in the MoS

layer. A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the device. The array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91% accuracy. This study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception

adaptive parallel processing networks for in-memory light sensing

and smart CCD cameras with artificial visual perception capabilities.

关键词

Keywords

references

Prezioso, M. et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors.Nature521, 61–64 (2015)..

Mennel, L. et al. Ultrafast machine vision with 2D material neural network image sensors.Nature579, 62–66 (2020)..

Zhu, J. H. et al. Analog circuit implementation of neural networks for in-sensor computing. InProc. 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 150–156 (IEEE, 2021).

Zhou, F. C. et al. Optoelectronic resistive random access memory for neuromorphic vision sensors.Nat. Nanotechnol.14, 776–782 (2019)..

Wang, Y. et al. MXene-ZnO memristor for multimodal in-sensor computing.Adv. Funct. Mater.31, 2100144 (2021)..

Liu, C. S. et al. A semi-floating gate memory based on van der Waals heterostructures for quasi-non-volatile applications.Nat. Nanotechnol.13, 404–410 (2018)..

Xiang, D. et al. Molecular-scale electronics: from concept to function.Chem. Rev.116, 4318–4440 (2016)..

Kim, S. et al. Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity.Nano Lett.15, 2203–2211 (2015)..

Zhou, Y. X. et al. Nonvolatile reconfigurable sequential logic in a HfO2resistive random access memory array.Nanoscale9, 6649–6657 (2017)..

Zhao, D. H. et al. Sensitive MoS2photodetector cell with high air-stability for multifunctional in-sensor computing.Chip1, 100023 (2022)..

Zhong, Y. N. et al. Synapse-like organic thin film memristors.Adv. Funct. Mater.28, 1800854 (2018)..

Xia, Q. F.&Yang, J. J. Memristive crossbar arrays for brain-inspired computing.Nat. Mater.18, 309–323 (2019)..

Shi, Y. Y. et al. Electronic synapses made of layered two-dimensional materials.Nat. Electron.1, 458–465 (2018)..

Lv, C. et al. Phase-change controlled magnetic tunnel junction for multifunctional in-sensor computing.IEEE Electron Device Lett.43, 482–485 (2022)..

Chai, Y.&Liao, F. Y.Near-Sensor and In-Sensor Computing(Springer, 2022).

Wang, M. et al. Author Correction: Robust memristors based on layered two-dimensional materials.Nat. Electron.1, 203 (2018)..

Lopez-Sanchez, O. et al. Ultrasensitive photodetectors based on monolayer MoS2.Nat. Nanotechnol.8, 497–501 (2013)..

Liao, F. Y. et al. Bioinspired in-sensor visual adaptation for accurate perception.Nat. Electron.5, 84–91 (2022)..

Hong, S. et al. Highly sensitive active pixel image sensor array driven by large-area bilayer MoS2transistor circuitry.Nat. Commun.12, 3559 (2021)..

Seo, S. et al. Artificial optic-neural synapse for colored and color-mixed pattern recognition.Nat. Commun.9, 5106 (2018)..

Lee, S. et al. Programmable black phosphorus image sensor for broadband optoelectronic edge computing.Nat. Commun.13, 1485 (2022)..

Shanmugam, V. et al. A review of the synthesis, properties, and applications of 2D materials.Part. Part. Syst. Charact.39, 2200031 (2022)..

Li, H. et al. Preparation and applications of mechanically exfoliated single-layer and multilayer MoS2and WSe2nanosheets.Acc. Chem. Res.47, 1067–1075 (2014)..

An, S. J. et al. Exfoliation of transition metal dichalcogenides by a high-power femtosecond laser.Sci. Rep.8, 12957 (2018)..

Matsuba, K. et al. Neat monolayer tiling of molecularly thin two-dimensional materials in 1 min.Sci. Adv.3, e1700414 (2017)..

Ganatra, R.&Zhang, Q. Few-layer MoS2: a promising layered semiconductor.ACS Nano8, 4074–4099 (2014)..

Hong, A. J. et al. Graphene flash memory.ACS Nano5, 7812–7817 (2011)..

Bertolazzi, S., Krasnozhon, D.&Kis, A. Nonvolatile memory cells based on MoS2/graphene heterostructures.ACS Nano7, 3246–3252 (2013)..

Zhang, E. Z. et al. Tunable charge-trap memory based on few-layer MoS2.ACS Nano9, 612–619 (2015)..

Yin, Z. Y. et al. Memory devices using a mixture of MoS2and graphene oxide as the active layer.Small9, 727–731 (2013)..

Liu, J. Q. et al. Preparation of MoS2-Polyvinylpyrrolidone nanocomposites for flexible nonvolatile rewritable memory devices with reduced graphene oxide electrodes.Small8, 3517–3522 (2012)..

Hong, X. et al. A universal method for preparation of noble metal nanoparticle-decorated transition metal dichalcogenide nanobelts.Adv. Mater.26, 6250–6254 (2014)..

Kang, M. J. Stable charge storing in two-dimensional MoS2nanoflake floating gates for multilevel organic flash memory.Nanoscale6, 12315–12323 (2014)..

Zhang, M. et al. MoS2-based charge-trapping synaptic device with electrical and optical modulated conductance.Nanophotonics9, 2475–2486 (2020)..

Gao, X. et al. Photon-energy-dependent light effects in organic nano-floating-gate nonvolatile memories.Org. Electron.15, 2486–2491 (2014)..

Han, S. T. et al. Poly(3-hexylthiophene)/gold nanoparticle hybrid system with an enhanced photoresponse for light-controlled electronic devices.Part. Part. Syst. Charact.30, 599–605 (2013)..

Dutta, S.&Narayan, K. S. Gate-voltage control of optically- induced charges and memory effects in polymer field-effect transistors.Adv. Mater.16, 2151–2155 (2004)..

Feng, C. G. et al. A pentacene field-effect transistor with light-programmable threshold voltage.Org. Electron.11, 1713–1718 (2010)..

Hu, Y. et al. Dependency of organic phototransistor properties on the dielectric layers.Appl. Phys. Lett.89, 072108 (2006)..

Choi, M. S. et al. Controlled charge trapping by molybdenum disulphide and graphene in ultrathin heterostructured memory devices.Nat. Commun.4, 1624 (2013)..

He, L. F. et al. Light-erasable embedded charge-trapping memory based on MoS2for system-on-panel applications.Appl. Phys. Lett.111, 223104 (2017)..

Hong, S. et al. Multifunctional molybdenum disulfide flash memory using a PEDOT: PSS floating gate.NPG Asia Mater.13, 38 (2021)..

Shin, M. et al. Charge-trapping memory device based on a heterostructure of MoS2and CrPS4.J. Korean Phys. Soc.78, 816–821 (2021)..

Chang, K. P. et al. Integration of fluorographene trapping medium in MoS2-based nonvolatile memory device.J. Appl. Phys.127, 245106 (2020)..

Wen, J. L. et al. Direct charge trapping multilevel memory with graphdiyne/MoS2van der Waals heterostructure.Adv. Sci.8, 2101417 (2021)..

Wang, S. P. et al. New floating gate memory with excellent retention characteristics.Adv. Electron. Mater.5, 1800726 (2019)..

Huang, C. C. et al. Scalable high-mobility MoS2thin films fabricated by an atmospheric pressure chemical vapor deposition process at ambient temperature.Nanoscale6, 12792 (2014)..

Patil, S. et al. Development of a novel method to grow mono-/few-layered MoS2films and MoS2–graphene hybrid films for supercapacitor applications.CrystEngComm16, 10845–10855 (2014)..

Lei, B., Li, G. R.&Gao, X. P. Morphology dependence of molybdenum disulfide transparent counter electrode in dye-sensitized solar cells.J. Mater. Chem. A2, 3919–3925 (2014)..

Laskar, M. R. et al. p-type doping of MoS2thin films using Nb.Appl. Phys. Lett.104, 092104 (2014)..

Senthilkumar, R. et al. One-step hydrothermal synthesis of marigold flower-like nanostructured MoS2as a counter electrode for dye-sensitized solar cells.J. Solid State Electrochem.22, 3331–3341 (2018)..

Wu, F. C. et al. Interface engineering via MoS2insertion layer for improving resistive switching of conductive-bridging random access memory.Adv. Electron. Mater.5, 1800747 (2019)..

Yang, J. et al. Wafer-scale synthesis of thickness-controllable MoS2films via solution-processing using a dimethylformamide/n-butylamine/2-aminoethanol solvent system.Nanoscale7, 9311–9319 (2015)..

Lou, S. N. et al. Oxygen nucleation of MoS2nanosheet thin film supercapacitor electrodes for enhanced electrochemical energy storage.ChemSusChem14, 2882–2891 (2021)..

Ji, H. M. et al. Rapid microwave-hydrothermal preparation of few-layer MoS2/C nanocomposite as anode for highly reversible lithium storage properties.J. Mater. Sci.53, 14548–14558 (2018)..

Chu, X. S. et al. Formation of MoO3and WO3nanoscrolls from MoS2and WS2with atmospheric air plasma.J. Mater. Chem. C5, 11301–11309 (2017)..

Ho, Y. T. et al. Layered MoS2grown onc-sapphire by pulsed laser deposition.Phys. Status Solidi Rapid Res. Lett.9, 187–191 (2015)..

Li, B. et al. Preparation of monolayer MoS2quantum dots using temporally shaped femtosecond laser ablation of bulk MoS2targets in water.Sci. Rep.7, 11182 (2017)..

Liu, H. et al. Perpendicular growth of few-layered MoS2nanosheets on MoO3nanowires fabricated by direct anion exchange reactions for high-performance lithium-ion batteries.J. Mater. Chem. A4, 17764–17772 (2016)..

Zhou, K. et al. Ultrathin MoO3nanocrystalsself-assembled on graphene nanosheets via oxygen bonding as supercapacitor electrodes of high capacitance and long cycle life.Nano Energy12, 510–520 (2015)..

Lu, X. et al. One-step hydrothermal fabrication of three-dimensional MoS2nanoflower using polypyrrole as template for efficient hydrogen evolution reaction.Sci. Rep.7, 42309 (2017)..

Liu, Y. J. et al. Growth and humidity-dependent electrical properties of bulk-like MoS2thin films on Si.RSC Adv.5, 74329–74335 (2015)..

Jia, H. et al. Large-scale arrays of single- and few-layer MoS2nanomechanical resonators.Nanoscale8, 10677–10685 (2016)..

Lee, Y. H. et al. Synthesis of large-area MoS2atomic layers with chemical vapor deposition.Adv. Mater.24, 2320–2325 (2012)..

Zhang, Y. et al. Defect states and charge trapping characteristics of HfO2films for high performance nonvolatile memory applications.Appl. Phys. Lett.105, 172902 (2014)..

Maikap, S. et al. Charge trapping characteristics of atomic-layer-deposited HfO2films with Al2O3as a blocking oxide for high-density non-volatile memory device applications.Semicond. Sci. Technol.22, 884–889 (2007)..

Shi, R. P. et al. Y-doped BaTiO3as a charge-trapping layer for nonvolatile memory applications.IEEE Electron Device Lett.37, 1555–1558 (2016)..

Huang, X. D., Sin, J. K. O.&Lai, P. T. Fluorinated SrTiO3as charge-trapping layer for nonvolatile memory applications.IEEE Trans. Electron Devices58, 4235–4240 (2011)..

Kim, T. H. et al. Electron trap density distribution of Si-rich silicon nitride extracted using the modified negative charge decay model of silicon-oxide-nitride-oxide-silicon structure at elevated temperatures.Appl. Phys. Lett.89, 063508 (2006)..

Xia, P. K. et al. Impact and origin of interface states in MOS capacitor with monolayer MoS2and HfO2high-kdielectric.Sci. Rep.7, 40669 (2017)..

Lin, Y. C. et al. Recent advances in organic phototransistors: nonvolatile memory, artificial synapses, and photodetectors.Small Sci.2, 2100109 (2022)..

Du, L. L. et al. High-performance organic broadband photomemory transistors exhibiting remarkable UV-NIR response.Phys. Chem. Chem. Phys.18, 13108–13117 (2016)..

Jiao, L. et al. Layer-dependent photoresponse of 2D MoS2films prepared by pulsed laser deposition.J. Mater. Chem. C7, 2522–2529 (2019)..

Fernández, O. et al. Photogenerated minority carrier trapping and inversion layer formation in polymer field-effect structures.IEEE Trans. Dielectr. Electr. Insul.13, 1093–1100 (2006)..

Kang, M. J. et al. Light-sensitive charge storage medium with spironaphthooxazine molecule-polymer blends for dual-functional organic phototransistor memory.Org. Electron.78, 105554 (2020)..

Choi, K. et al. Trap density probing on top-gate MoS2nanosheet field-effect transistors by photo-excited charge collection spectroscopy.Nanoscale7, 5617–5623 (2015)..

Krizhevsky, A.Learning Multiple Layers of Features from Tiny Images(University of Toronto, 2009).

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

暂无数据

Artificial visual perception neural system using a solution-processable MoS2-based in-memory light sensor

Artificial visual perception neural system using a solution-processable MoS2-based in-memory light sensor

DOI：10.1038/s41377-023-01166-7

摘要

Abstract

关键词

Keywords

references

Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor

Artificial visual perception neural system using a solution-processable MoS₂-based in-memory light sensor