1. Application of Machine Learning to the Design of Energetic Materials: Preliminary Experience and Comparison with Alternative Techniques. Issue 4 (11th January 2023) Authors: Wespiser, Clément; Mathieu, Didier Journal: Propellants, explosives, pyrotechnics Issue: Volume 48:Issue 4(2023) Page Start: n/a Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Erratum: Modeling Sensitivities of Energetic Materials using the Python Language and Libraries. Issue 2 (3rd February 2022) Authors: Mathieu, Didier Journal: Propellants, explosives, pyrotechnics Issue: Volume 47:Issue 2(2022) Page Start: n/a Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. General estimation method for lower flammability limits of organic compounds: The simpler the better. (15th June 2023) Authors: Maury, Mathilda; Mathieu, Didier; Jacquemin, Johan Journal: Fuel Issue: Volume 342(2023) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. Impact sensitivities of energetic materials derived from easy-to-compute ab initio rate constants. Issue 15 (29th March 2023) Authors: Claveau, Romain; Glorian, Julien; Mathieu, Didier Journal: Physical chemistry chemical physics Issue: Volume 25:Issue 15(2023) Page Start: 10550 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. Improved model for the refractive index: application to potential components of ambient aerosol. Issue 34 (15th August 2018) Authors: Bouteloup, Rémi; Mathieu, Didier Journal: Physical chemistry chemical physics Issue: Volume 20:Issue 34(2018) Page Start: 22017 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. Modeling Sensitivities of Energetic Materials using the Python Language and Libraries. Issue 6 (21st February 2020) Authors: Mathieu, Didier Journal: Propellants, explosives, pyrotechnics Issue: Volume 45:Issue 6(2020) Page Start: 966 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. Molecular Energies Derived from Deep Learning: Application to the Prediction of Formation Enthalpies Up to High Energy Compounds. Issue 5 (10th December 2021) Authors: Mathieu, Didier Journal: Molecular informatics Issue: Volume 41:Issue 5(2022) Page Start: n/a Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. Predicting dielectric constants of pure liquids: fragment-based Kirkwood–Fröhlich model applicable over a wide range of polarity. Issue 21 (15th May 2019) Authors: Bouteloup, Rémi; Mathieu, Didier Journal: Physical chemistry chemical physics Issue: Volume 21:Issue 21(2019) Page Start: 11043 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. QSPR versus fragment-based methods to predict octanol-air partition coefficients: Revisiting a recent comparison of both approaches. (April 2020) Authors: Mathieu, Didier Journal: Chemosphere Issue: Volume 245(2020) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
10. Significance of Theoretical Decomposition Enthalpies for Predicting Thermal Hazards. (18th June 2015) Authors: Mathieu, Didier Other Names: Zaleśny Robert Academic Editor. Journal: Journal of chemistry Issue: Volume 2015(2015) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗