Evidence map›Paper›PMID 38320750›Full record

ArticleACS sensors2024

Optimized Detection of Volatile Organic Compounds Utilizing Durable and Selective Arrays of Tailored UiO-66-X SURMOF Sensors.

Salih Okur, Tawheed Hashem, Evgenia Bogdanova, Patrick Hodapp, Lars Heinke, Stefan Bräse, Christof Wöll

Open access · greenAbstract read
In one paragraph

Article in ACS sensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.8field-weighted citation impact, top 3% 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

4 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Specific Identification ofFoods (Basel, Switzerland) · 2025
    Article
  3. Review
  4. 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

7 authors at 1 institution in 1 country.

Salih OkurKarlsruhe Institute of Technology (KIT), Institute of Functional Interfaces, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.
Tawheed HashemKarlsruhe Institute of Technology (KIT), Institute of Functional Interfaces, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.
Evgenia BogdanovaKarlsruhe Institute of Technology (KIT), Institute of Functional Interfaces, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.
Patrick HodappKarlsruhe Institute of Technology (KIT), Institute for Biological Interfaces 3-Soft Matter Synthesis Laboratory (IBG3-SML), Kaiserstrasse 12, 76131 Karlsruhe, Germany.
Lars HeinkeKarlsruhe Institute of Technology (KIT), Institute of Functional Interfaces, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.ORCID 0000-0002-1439-9695
Stefan BräseKarlsruhe Institute of Technology (KIT), Institute of Organic Chemistry (IOC), Kaiserstrasse 12,, 76131 Karlsruhe, Germany.ORCID 0000-0003-4845-3191
Christof WöllKarlsruhe Institute of Technology (KIT), Institute of Functional Interfaces, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.ORCID 0000-0003-1078-3304
Karlsruhe Institute of Technology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metal-organic frameworks (MOFs), with their well-defined and highly flexible nanoporous architectures, provide a material platform ideal for fabricating sensors. We demonstrate that the efficacy and specificity of detecting and differentiating volatile organic compounds (VOCs) can be significantly enhanced using a range of slightly varied MOFs. These variations are obtained via postsynthetic modification (PSM) of a primary framework. We alter the original MOF's guest adsorption affinities by incorporating functional groups into the MOF linkers, which yields subtle changes in responses. These responses are subsequently evaluated by using machine learning (ML) techniques. Under severe conditions, such as high humidity and acidic environments, sensor stability and lifespan are of utmost importance. The UiO-66-X MOFs demonstrate the necessary durability in acidic, neutral, and basic environments with pH values ranging from 2 to 11, thus surpassing most other similar materials. The UiO-66-NH

Indexed as

Metal-Organic FrameworksPhthalic AcidsVolatile Organic CompoundsAdsorptionMetal-Organic FrameworksPhthalic AcidsUiO-66Volatile Organic Compoundsdiscriminationelectronic noseharsh conditionslayer-by-layerMOFstabilitySURMOFVOC

Identifiers

PMID38320750
PMCPMC10898453
OpenAlexW4391612592

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.