Evidence map›Paper›PMID 40274790›Full record

ArticleNature communications2025

Ultra-weak infrared light detection based on steep-slope phototransistors.

Jiadong Mei, Junzhuan Wang, Xuetao Gan, Xiaomu Wang

Abstract read
In one paragraph

Article in Nature communications, 2025. 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. 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

4 authors.

Jiadong MeiSchool of Electronic Science and Engineering, Nanjing University, Nanjing, China.
Junzhuan WangSchool of Electronic Science and Engineering, Nanjing University, Nanjing, China. wangjz@nju.edu.cn.ORCID http://orcid.org/0000-0003-1851-220X
Xuetao GanKey Laboratory of Light Field Manipulation and Information Acquisition, Ministry of Industry and Information Technology, Shaanxi Key Laboratory of Optical Information Technology, School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an, China.ORCID http://orcid.org/0000-0003-2469-5807
Xiaomu WangSchool of Electronic Science and Engineering, Nanjing University, Nanjing, China. xiaomu.wang@nju.edu.cn.ORCID http://orcid.org/0000-0001-8975-5626

Funding

National Science Foundation of China | National Natural Science Foundation of China-Yunnan Joint Fund (NSFC-Yunnan Joint Fund) 61934004National Science Foundation of China | National Natural Science Foundation of China-Yunnan Joint Fund (NSFC-Yunnan Joint Fund) 62325404
6 · The paper itself

Abstract

A photodetector's sensitivity is conventionally quantified by specific detectivity, which balances responsivity and noise. However, we reveal that the turn-on threshold power is fundamentally governed by photo-carrier injection rather than detectivity. In conventional phototransistors/diodes, incident light cannot generate photocurrent via thermionic injection until its intensity saturates the surface potential. To overcome this limit, we design a photo-tunneling transistor with a partially dual-gated black phosphorus channel. This device breaks the injection barrier, achieving a temperature-independent subthreshold swing of ~50 mV/dec up to 250 K and reducing the threshold power by over an order of magnitude. At 80 K, it detects mid-wave infrared light with a minimum power of ~35 pW, outperforming conventional phototransistors with higher detectivity by ~30-fold. Our work redefines the sensitivity criteria for photodetectors and highlights the potential of steep-slope transistors in low-power optoelectronics, offering a pathway to ultrasensitive infrared sensing and imaging technologies.

Identifiers

PMID40274790
PMCPMC12022149

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.