Evidence map›Paper›PMID 33799595›Full record

ArticleMicromachines2021

A Microfluidic Device for Automated High Throughput Detection of Ice Nucleation of Snomax

Priyatanu Roy, Margaret L House, Cari S Dutcher

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

6 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. A highly active mineral-based ice nucleating agent supportsJournal of the Royal Society, Interface · 2023
    Article
  6. 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

3 authors at 1 institution in 1 country.

Priyatanu RoyDepartment of Mechanical Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.ORCID 0000-0002-7299-9306
Margaret L HouseDepartment of Chemical Engineering & Materials Science, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.
Cari S DutcherDepartment of Mechanical Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.ORCID 0000-0003-4325-9197
University of Minnesota · US

Funding

National Science Foundation CHE1801971National Science Foundation ECCS2025124
6 · The paper itself

Abstract

Measurement of ice nucleation (IN) temperature of liquid solutions at sub-ambient temperatures has applications in atmospheric, water quality, food storage, protein crystallography and pharmaceutical sciences. Here we present details on the construction of a temperature-controlled microfluidic platform with multiple individually addressable temperature zones and on-chip temperature sensors for high-throughput IN studies in droplets. We developed, for the first time, automated droplet freezing detection methods in a microfluidic device, using a deep neural network (DNN) and a polarized optical method based on intensity thresholding to classify droplets without manual counting. This platform has potential applications in continuous monitoring of liquid samples consisting of aerosols to quantify their IN behavior, or in checking for contaminants in pure water. A case study of the two detection methods was performed using Snomax

Indexed as

automated detectiondeep neural networkhigh-throughputice nucleating particlemachine learningmicrofluidic devicepolarized lightSnomax®

Identifiers

PMID33799595
PMCPMC7998955
OpenAlexW3137267428

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.