Evidence map›Paper›PMID 35842450›Full record

ArticleScientific reports2022

A novel hardmask-to-substrate pattern transfer method for creating 3D, multi-level, hierarchical, high aspect-ratio structures for applications in microfluidics and cooling technologies.

Sougata Hazra, Chi Zhang, Qianying Wu, Mehdi Asheghi, Kenneth Goodson, Ercan M Dede, James Palko, Sreekant Narumanchi

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

8 authors.

Sougata HazraDepartment of Mechanical Engineering, Stanford University, Stanford, USA. shazra@stanford.edu.
Chi ZhangDepartment of Mechanical Engineering, Stanford University, Stanford, USA.
Qianying WuDepartment of Mechanical Engineering, Stanford University, Stanford, USA.
Mehdi AsheghiDepartment of Mechanical Engineering, Stanford University, Stanford, USA.
Kenneth GoodsonDepartment of Mechanical Engineering, Stanford University, Stanford, USA.
Ercan M DedeElectronics Research Department, Toyota Research Institute of North America, Ann Arbor, MI, USA.
James PalkoDepartment of Mechanical Engineering, University of California-Merced, Merced, CA, USA.
Sreekant NarumanchiNational Renewable Energy Laboratory, Golden, CO, USA.

Funding

Advanced Research Projects Agency - Energy DE-AR0001055
6 · The paper itself

Abstract

This letter solves a major hurdle that mars photolithography-based fabrication of micro-mesoscale structures in silicon. Conventional photolithography is usually performed on smooth, flat wafer surfaces to lay a 2D design and subsequently etch it to create single-level features. It is, however, unable to process non-flat surfaces or already etched wafers and create more than one level in the structure. In this study, we have described a novel cleanroom-based process flow that allows for easy creation of such multi-level, hierarchical 3D structures in a substrate. This is achieved by introducing an ultra-thin sacrificial silicon dioxide hardmask layer on the substrate which is first 3D patterned via multiple rounds of lithography. This 3D pattern is then scaled vertically by a factor of 200-300 and transferred to the substrate underneath via a single shot deep etching step. The proposed method is also easily characterizable-using features of different topographies and dimensions, the etch rates and selectivities were quantified; this characterization information was later used while fabricating specific target structures. Furthermore, this study comprehensively compares the novel pattern transfer technique to already existing methods of creating multi-level structures, like grayscale lithography and chip stacking. The proposed process was found to be cheaper, faster, and easier to standardize compared to other methods-this made the overall process more reliable and repeatable. We hope it will encourage more research into hybrid structures that hold the key to dramatic performance improvements in several micro-mesoscale devices.

Identifiers

PMID35842450
PMCPMC9288478

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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.