Evidence map›Paper›PMID 42577846›Full record

ArticleNational science review2026

Ultralow-dose X-ray imaging enabled by vertically homogeneous perovskite films.

Zhiqiang Liu, Jincong Pang, Ziling Zhou, Hao Chen, Qinghao Ling, Chenxing Li, Yuanpeng Shi, Zhuangzhuang Yang, Ling Xu, Zhiping Zheng and 4 more

Abstract read
In one paragraph

Article in National science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Zhiqiang LiuOptical Valley Laboratory, Wuhan 430074, China.
Jincong PangOptical Valley Laboratory, Wuhan 430074, China.
Ziling ZhouDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Hao ChenWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Qinghao LingWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Chenxing LiWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Yuanpeng ShiWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Zhuangzhuang YangSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China.
Ling XuWuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
Zhiping ZhengSchool of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China.
Zhen LiDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Jiang TangOptical Valley Laboratory, Wuhan 430074, China.ORCID https://orcid.org/0000-0003-2574-2943
Xiaoping OuyangNorthwest Institute of Nuclear Technology, Xi'an 710024, China.
Guangda NiuOptical Valley Laboratory, Wuhan 430074, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence is rapidly pushing imaging and sensing toward automated, quantitative decision-making, heightening the demand for reliable low-photon-flux detection and imaging across infrared through X-ray regimes, yet developing detectors that truly operate effectively at ultralow photon fluxes has been a challenge. As a canonical instance, low-dose X-ray imaging operates under intrinsically sparse photon statistics, where Poisson fluctuations along the absorption depth couple to vertical transport non-uniformity and are statistically amplified at ultralow dose. Here we elucidate this materials-to-electronics bottleneck and develop a new liquid-phase growth and annealing strategy that eliminates thermal and mass-transport instabilities in conventional methods during crystallization, yielding perovskite films with exceptional vertical uniformity. This enables depth-independent charge collection, significantly reducing stochastic fluctuations in the readout and achieving a 10-fold reduction in image noise. In imaging applications, our detectors deliver high-quality X-ray imaging at an ultralow effective per-pixel integration dose of 40.6 nGy

Indexed as

liquid-phase growth and annealinglow-dose X-ray imagingultralow photon fluxesvertical uniformity

Identifiers

PMID42577846
PMCPMC13455612

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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.