Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor.

Jingxi Li, Xurong Li, Nezih T Yardimci, Jingtian Hu, Yuhang Li, Junjie Chen, Yi-Chun Hung, Mona Jarrahi, Aydogan Ozcan

Abstract read

In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it

0cells of the map it votes in

8citing 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

8 citing papers in PubMed.

Spatiotemporal information fusion for photon-level dynamic imaging.Scientific reports · 2026
Article
Ultrafast Dynamic Defect Inspection With Computational Neuromorphic Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
Article
Ultrahigh-throughput single-pixel complex-field microscopy with frequency-comb acousto-optic coherent encoding (FACE).Light, science & applications · 2025
Article
Current State of the Art and Potential for Construction and Demolition Waste Processing: A Scoping Review of Sensor-Based Quality Monitoring and Control for In- and Online Implementation in Production Processes.Sensors (Basel, Switzerland) · 2025
Review
Universal point spread function engineering for 3D optical information processing.Light, science & applications · 2025
Article
Optical neural networks: progress and challenges.Light, science & applications · 2024
Review
All-optical complex field imaging using diffractive processors.Light, science & applications · 2024
Article
High-throughput terahertz imaging: progress and challenges.Light, science & applications · 2023
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

9 authors.

Jingxi LiElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID http://orcid.org/0000-0001-6595-8680

Xurong LiElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID http://orcid.org/0000-0003-3770-723X

Nezih T YardimciElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID http://orcid.org/0000-0002-3623-5835

Jingtian HuElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.

Yuhang LiElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.

Junjie ChenPhysics & Astronomy Department, University of California, Los Angeles, CA, 90095, USA.

Yi-Chun HungElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.

Mona JarrahiElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID http://orcid.org/0000-0001-9514-555X

Aydogan OzcanElectrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA. ozcan@ucla.edu.ORCID http://orcid.org/0000-0002-0717-683X

Funding

United States Department of Defense | United States Navy | Office of Naval Research (ONR) N00014-22-1-2016U.S. Department of Energy (DOE) DE-SC0016925

6 · The paper itself

Abstract

Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Furthermore, machine-vision-based systems using large-pixel-count imaging encounter bottlenecks due to their data storage, transmission and processing requirements. Here, we report a diffractive sensor that rapidly detects hidden defects/objects within a 3D sample using a single-pixel terahertz detector, eliminating sample scanning or image formation/processing. Leveraging deep-learning-optimized diffractive layers, this diffractive sensor can all-optically probe the 3D structural information of samples by outputting a spectrum, directly indicating the presence/absence of hidden structures or defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing and industrial quality control.

Identifiers

PMID37880258

DOI10.1038/s41467-023-42554-2

PMCPMC10600253

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.