ArticleChemistry (Weinheim an der Bergstrasse, Germany)2025
Data-Driven Polyoxometalate Chemistry.
Article in Chemistry (Weinheim an der Bergstrasse, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
5 authors.
Funding
Abstract
Polyoxometalates (POMs) are nanoscale, structurally versatile metal-oxo clusters with emerging applications in sustainability, energy, nanoelectronics, and life science technologies. Owing to their structural complexity, some all-inorganic POMs are often perceived as serendipitous outcomes from self-assembly processes, which poses challenges for scalable rational design. From this perspective, we therefore examine how the development of POM informatics and, more generally, data-driven POM exploration can pave the way for the molecular engineering of new POM-based materials targeting customized applications. In the process, we highlight recent successes in the digitalization of POM chemistry and outline which advanced technologies are necessary for progress in this promising area of research.
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Registered trials
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.