Evidence map›Paper›PMID 41877521›Full record

ArticleInorganic chemistry2026

High-Throughput Microscale MOF Catalysis via Solid Dispersion Reactor Dosing.

Shuxiao Li, John C Izang, Jesse B Duque, Garry D Leonard, James R Bour

Abstract read
In one paragraph

Article in Inorganic chemistry, 2026. 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

5 authors.

Shuxiao LiDepartment of Chemistry, Wayne State University, 5101 Cass Ave., Detroit, Michigan 48202, United States.
John C IzangDepartment of Chemistry, Wayne State University, 5101 Cass Ave., Detroit, Michigan 48202, United States.
Jesse B DuqueDepartment of Chemistry, Wayne State University, 5101 Cass Ave., Detroit, Michigan 48202, United States.
Garry D LeonardDepartment of Chemistry, Wayne State University, 5101 Cass Ave., Detroit, Michigan 48202, United States.
James R BourDepartment of Chemistry, Wayne State University, 5101 Cass Ave., Detroit, Michigan 48202, United States.ORCID 0000-0002-0372-7323

Funding

Materials and Macromolecules Tailored for Micro and Nanoscale Organic SynthesisR35GM157057 · NIGMS · WAYNE STATE UNIVERSITY · PI James Bour · 2025 to 2026
$931k
NIGMS NIH HHS R35 GM157057
6 · The paper itself

Abstract

Metal-organic frameworks (MOFs) exhibit exceptional structural diversity and tunable chemical environments, offering excellent opportunities for tuning the selectivity of catalytic centers confined to their pores. As such, MOF catalysts have been shown to exhibit distinct size-, regio-, and chemoselectivity relative to those of other heterogeneous platforms. Despite these advantages, the discovery and optimization of highly active and selective MOF catalysts for complex transformations remain challenging. Their poor solubility, low bulk density, and mechanical fragility complicate their integration into small-scale, high-throughput (HT) experiments that would otherwise facilitate catalyst optimization. In this work, we present the adaptation of inexpensive bead-based reactor dosing methodologies to overcome these limitations. A central feature of this strategy is the development of plate-reader-based analysis of reactor dosing, which enables the rapid optimization of MOF-bead formulations for accurate and precise well-to-well dosing. The utility of this approach is demonstrated in a proof-of-concept study involving the identification and optimization of a novel MOF-catalyzed C-H oxidation reaction, thereby establishing an accessible workflow for accelerating the development of MOF catalysts in batch reaction formats.

Identifiers

PMID41877521
PMCPMC13142244

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Registered trials

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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.