Evidence map›Paper›PMID 41761696›Full record

ArticleSmall methods2026

Particle-Based Detection of Surface Chemistry via Optical Microscopy-Integrating Microfluidics, Light-Induced Activity of Colloids and Data Science.

Fabian Rohne, Daniela Vasquez Muñoz, Isabel Meier, Anne Nitschke, Florian Schmitt, Nino Lomadze, Martin Reifarth, Andreas Taubert, Svetlana Santer, Marek Bekir

Abstract read
In one paragraph

Article in Small methods, 2026. 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

10 authors.

Fabian RohneInstitute of Physics and Astronomy, University Potsdam, Potsdam, Germany.ORCID https://orcid.org/0009-0000-2162-1824
Daniela Vasquez MuñozInstitute of Physics and Astronomy, University Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0003-3212-8415
Isabel MeierInstitute of Physics and Astronomy, University Potsdam, Potsdam, Germany.
Anne NitschkeInstitute of Chemistry, University Potsdam, Potsdam, Germany.
Florian SchmittInstitute of Chemistry, Fraunhofer Institute of Applied Polymer Research, University Potsdam, Potsdam, Germany.
Nino LomadzeInstitute of Physics and Astronomy, University Potsdam, Potsdam, Germany.
Martin ReifarthInstitute of Chemistry, Fraunhofer Institute of Applied Polymer Research, University Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-2260-3510
Andreas TaubertInstitute of Chemistry, University Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-9329-0072
Svetlana SanterInstitute of Physics and Astronomy, University Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-5041-3650
Marek BekirInstitute of Physics and Astronomy, University Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-6989-9996

Funding

DFG 469240574DFG 471323994
6 · The paper itself

Abstract

We present particle-resolved methods for determining the porosity and surface area of microparticles, based on single-particle trajectory analysis conducted via optical video microscopy integrated with microfluidics and LED illumination. This technique introduces a unique combination of analytical advantages that address key limitations of conventional methods, such as BET nitrogen adsorption. Notably, (1) the method operates with extremely low analyte quantities on the order of micrograms or less and in the form of dilute aqueous dispersions, eliminating the need for drying or bulk sample preparation; (2) surface area quantification is performed on a per-particle basis, with total surface area determined by summing up all individual particle measurements, enabling high-resolution analysis of particle-to-particle heterogeneity; and (3) the entire workflow from sample preparation to data acquisition and surface area calculation is rapid, straightforward, and relies only on a pre-defined, self-generated reference data library. We validate the method using both plain and mesoporous SiO

Indexed as

colloid sensorsparticle‐based porosity determinationphotosensitive surfactantssurface area determinationunsupervised machine learning

Identifiers

PMID41761696
PMCPMC13010204

What Socratic 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 Socratic graph.