Evidence map›Paper›PMID 40248045›Full record

ArticleAdvanced materials technologies2025

A Subtractive Method to Chemically Pattern Liquid Metal for Stretchable Circuits.

Kaushal Sumaria, Tingyi Leo Liu

Abstract read
In one paragraph

Article in Advanced materials technologies, 2025. 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

2 authors.

Kaushal SumariaDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003, USA.
Tingyi Leo LiuDepartment of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003, USA.

Funding

Engineering of Stretchable Neural Interfaces Using Liquid Metals for Stable Electrical Communication and Adaptive Stiffness TransformationR21EB033599 · NIBIB · UNIVERSITY OF MASSACHUSETTS AMHERST · PI LIU, TINGYI · 2023 to 2025
$613k
NIBIB NIH HHS R21 EB033599
6 · The paper itself

Abstract

Advancements in biomedical research have spurred the development of stretchable electronic devices. While soft insulators are readily available, soft conductors with metal-like electrical conductivity are rare. Gallium and its alloys, being non-toxic and intrinsically stretchable, are potentially ideal solutions. However, current additive liquid metal (LM) patterning methods face limitations in achieving high-throughput, high-resolution, and high-density LM wiring. Here, a subtractive LM patterning method has been developed to meet all these requirements simultaneously. The innovative method involves parallel filling a single continuous microfluidic mesh network with LM that short-circuits all the pins and pads of a circuit, followed by parallel cutting of the unwanted short-circuited interconnections using hydrochloric acid (HCl) vapor. Cutting locations are pre-defined by designing narrower intersecting channels, leveraging capillary force for precise filling and cutting. The process was characterized using a multi-dimensional parametric study with varying LM line widths and HCl concentrations, and in-situ impedance measurements to assess insulation performance. To showcase its high-throughput capabilities, a mock circuit was used to successfully generate complex LM interconnects that connected hundreds of electrical pads. Lastly, a stretchable LM circuit, fabricated using the subtractive LM patterning method, was integrated with a micro-LED array, highlighting the practical application of this new technology in creating massively parallel LM wirings in complex, heterogeneous, and stretchable electronic circuits.

Indexed as

Liquid metalsmicrofluidicsstretchable electronics

Identifiers

PMID40248045
PMCPMC12002554

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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.