Evidence map›Paper›PMID 39521838›Full record

ArticleScientific reports2024

Mitigating coherent loss in superconducting circuits using molecular self-assembled monolayers.

Mohammed Alghadeer, Archan Banerjee, Kyunghoon Lee, Hussein Hussein, Hossein Fariborzi, Saleem Rao

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Mohammed AlghadeerDepartment of Physics, University of California, Berkeley, CA, 94720, USA. ghadeer@berkeley.edu.
Archan BanerjeeDepartment of Physics, University of California, Berkeley, CA, 94720, USA.
Kyunghoon LeeDepartment of Physics, University of California, Berkeley, CA, 94720, USA.
Hussein HusseinCEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Hossein FariborziCEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Saleem RaoDepartment of Physics, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia. saleemg@kfupm.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In planar superconducting circuits, decoherence due to materials imperfections, especially two-level-system (TLS) defects at different interfaces, is a primary hurdle for advancing quantum computing and sensing applications. Traditional methods for mitigating TLS loss, such as etching oxide layers at metal and substrate interfaces, have proven to be inadequate due to the persistent challenge of oxide regrowth. In this work, we introduce a novel approach that employs molecular self-assembled monolayers (SAMs) to chemically bind at different interfaces of superconducting circuits. This technique is specifically tested here on coplanar waveguide (CPW) resonators, in which this method not only impedes oxide regrowth after surface etching but can also tailors the dielectric properties at different resonators interfaces. The deployment of SAMs results in a consistent improvement in the measured quality factors across multiple resonators, surpassing those with only oxide-etched resonators. The efficiency of our approach i3s supported by microwave measurements of multiple devices conducted at millikelvin temperatures and correlated with detailed X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) characterizations of SAM-passivated resonators. The compatibility of SAMs materials with the established fabrication techniques offers a promising route to improve the performance of superconducting quantum devices.

Identifiers

PMID39521838
PMCPMC11550477

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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.