ArticleRSC advances2026
Monte Carlo-based QSPR modeling of drop-weight impact sensitivity of energetic materials using hybrid SMILES-graph descriptors.
Article in RSC advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Impact sensitivity under mechanical stimuli is one of the most crucial safety properties of energetic materials. The drop-weight test is a common method for evaluating the impact sensitivity of explosives, with results typically reported as the 50% initiation height (
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Registered trials
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