QsarDB
metadata only
Prana, V.; Rotureau, P.; André, D.; Fayet, G.; Adamo, C. Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides. Mol. Inform. 2017, 36, 1700024.
Quantitative structure‐property relationships represent alternative method to experiments to access the estimation of physico‐chemical properties of chemicals for screening purpose at R&D level but also to gather missing data in regulatory context. In particular, such predictions were encouraged by
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Pan, Y.; Zhang, Y.; Jiang, J.; Ding, L. Prediction of the self-accelerating decomposition temperature of organic peroxides using the quantitative structure–property relationship (QSPR) approach. J. Loss Prev. Process Ind. 2014, 31, 41–49.#933056
- Discovering Kinetically Significant Reaction Mechanisms Beyond Chemical Intuition in Condensed-Phase Radiolysis#1122546
- Daga, P. ADMET Predictor - Bacterial mutagenicity model (MUT_m102+wp2). 2020.#933239
- Daga, P. ADMET Predictor - Bacterial mutagenicity model (MUT_102+wp2). 2020.#933129
- Daga, P. ADMET Predictor - Bacterial mutagenicity model (MUT_98). 2020.#933050
Record · ID 933140
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive