Multi‐Functional Metasurfaces as a Platform to Realize Ultra‐Compact Confocal Instrumentation for on‐Machine Metrology

Abstract As manufacturing looks to employ more smart and autonomous processes to improve how items are made, reducing scrappage rates and with it the associated waste of time and energy, new ultra‐compact sensors are needed that can be deployed where existing instrumentation cannot. The use of traditional methods when constructing optical sensors limits the progress that can be made in reducing their size and weight, however, emerging technologies such as metasurfaces offer a platform by which these barriers can be overcome to develop the sensors needed to underpin this manufacturing transition. Here it is demonstrated that how a single metasurface can be used to deliver all the optical manipulations required to create a metasurface‐based confocal sensor with only the addition of a point source and point detector. By combining the optical functionality of both the illumination and the collection optics in this way the system is simplified and reduced in size significantly. While here how a metasurface can be used to reduce the number of elements needed to produce an ultra‐compact confocal sensor is demonstrated, this approach can be used to simplify a far wider range of instrumentation to greatly reduce their size and weight.

Authors

Institutions

Publication Details

Journal
Advanced Materials Technologies
Published
2024-08-31
DOI
https://doi.org/10.1002/admt.202400387
Citations
2
Primary Topic
Random lasers and scattering media
Type
article
Field-Weighted Citation Impact
0.55

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi‐Functional Metasurfaces as a Platform to Realize Ultra‐Compact Confocal Instrumentation for on‐Machine Metrology

Haydn Martin, James Williamson, Xiangqian Jiang, Daniel J. Townend et al.
2 citations
Advanced Materials Technologies
Random lasers and scattering media
0.55
article

Multi‐Functional Metasurfaces as a Platform to Realize Ultra‐Compact Confocal Instrumentation for on‐Machine Metrology

Haydn Martin, James Williamson, Xiangqian Jiang, Daniel J. Townend, Andrew Henning
article en
2 citations

Abstract

Abstract As manufacturing looks to employ more smart and autonomous processes to improve how items are made, reducing scrappage rates and with it the associated waste of time and energy, new ultra‐compact sensors are needed that can be deployed where existing instrumentation cannot. The use of traditional methods when constructing optical sensors limits the progress that can be made in reducing their size and weight, however, emerging technologies such as metasurfaces offer a platform by which these barriers can be overcome to develop the sensors needed to underpin this manufacturing transition. Here it is demonstrated that how a single metasurface can be used to deliver all the optical manipulations required to create a metasurface‐based confocal sensor with only the addition of a point source and point detector. By combining the optical functionality of both the illumination and the collection optics in this way the system is simplified and reduced in size significantly. While here how a metasurface can be used to reduce the number of elements needed to produce an ultra‐compact confocal sensor is demonstrated, this approach can be used to simplify a far wider range of instrumentation to greatly reduce their size and weight.

Advanced Materials TechnologiesVol. 10(4)
University of Huddersfield (GB)
Royal Academy of Engineering, Engineering and Physical Sciences Research Council
Affordable and clean energy
Openalex Percentile: Top 42%
Random lasers and scattering media
0.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.