Evidence map›Paper›PMID 39604389›Full record

ArticleNature communications2024

Programmable nonlinear optical neuromorphic computing with bare 2D material MoS

Lei Tong, Yali Bi, Yilun Wang, Kai Peng, Xinyu Huang, Wei Ju, Zhuiri Peng, Zheng Li, Langlang Xu, Runfeng Lin and 15 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

25 authors.

Lei Tong *School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yali Bi *Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yilun Wang *School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID http://orcid.org/0000-0001-9416-2219
Kai PengDepartment of Materials Science and Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.ORCID http://orcid.org/0000-0002-6437-0516
Xinyu HuangSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Wei JuSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zhuiri PengSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Zheng LiSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Langlang XuSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Runfeng LinSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Xiangxiang YuSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Wenhao ShiSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID http://orcid.org/0009-0006-3855-0464
Hui YuDepartment of Electronic Engineering, Materials Science and Technology Research Center, The Chinese University of Hong Kong, Hong Kong, China.
Huajun SunSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Kanhao XueSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID http://orcid.org/0000-0002-2894-7912
Qiang HeSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID http://orcid.org/0000-0002-6252-7030
Ming TangSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID http://orcid.org/0000-0001-8669-4186
Jianbin XuDepartment of Electronic Engineering, Materials Science and Technology Research Center, The Chinese University of Hong Kong, Hong Kong, China.ORCID http://orcid.org/0000-0003-0509-9508
Xinliang ZhangSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID http://orcid.org/0000-0001-8513-3328
Jinshui MiaoState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0000-0002-3041-1105
Deep JariwalaDepartment of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID http://orcid.org/0000-0002-3570-8768
Wei BaoDepartment of Materials Science and Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA. baow2@rpi.edu.ORCID http://orcid.org/0000-0003-2974-2625
Xiangshui MiaoSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China. miaoxs@hust.edu.cn.ORCID http://orcid.org/0000-0002-3999-7421
Ping WangSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China. p_wang@hust.edu.cn.ORCID http://orcid.org/0000-0002-5168-6829
Lei YeSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan, Hubei, China. leiye@hust.edu.cn.ORCID http://orcid.org/0000-0001-5195-1867

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nonlinear optical responses in two-dimensional (2D) materials can build free-space optical neuromorphic computing systems. Ensuring the high performance and the tunability of the system is essential to encode diverse functions. However, common strategies, including the integration of external electrode arrays or photonic structures with 2D materials, and barely patterned 2D materials, exhibit a contradiction between performance and tunability. Because the unique band dispersions of 2D materials can provide hidden paths to boost nonlinear responses independently, here we introduced a new free-space optical computing concept within a bare molybdenum disulfide array. This system can preserve high modulation performance with fast speed, low energy consumption, and high signal-to-noise ratio. Due to the freedom from the restrictions of fixed photonic structures, the tunability is also enhanced through the synergistic encodings of the 2D cells and the excitation pulses. The computing mechanism of transition from two-photon absorption to synergistic excited states absorption intrinsically improved the modulation capability of nonlinear optical responses, revealed from the relative transmittance modulated by a pump-probe-control strategy. Optical artificial neural network (ANN) and digital processing were demonstrated, revealing the feasibility of the free-space optical computing based on bare 2D materials toward neuromorphic applications.

Identifiers

PMID39604389
PMCPMC11603154

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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.