Application of machine learning in developing a quantitative structure–property relationship model for predicting the thermal decomposition temperature of nitrogen-rich energetic ionic salts
RSC Advances,
Год журнала:
2024,
Номер
14(51), С. 37737 - 37751
Опубликована: Янв. 1, 2024
A
reliable
QSPR
model
of
thermal
decomposition
temperature
(
T
d
)
was
built
and
developed
using
support
vector
machine
(SVM)
learning
technology
to
predict
the
property
newly
designed
nitrogen-rich
energetic
ionic
salts.
Язык: Английский
High-Energy and Thermally Stable Energetic Materials Based on an Azo-Fused Dinitramino Compound
Teng Zhu,
Chengchuang Li,
Jie Tang
и другие.
Organic Letters,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 23, 2024
Here,
azo-fused
dinitramino
energetic
compound
5,5'-dinitramino-8,8'-azo-1,2,5-oxadiazolo[3,4-
Understanding of the Bond Dissociation Energy of C-NO2 in Five- and Six-Membered N-Heteroaromatic Derivatives
FirePhysChem,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 1, 2024
Язык: Английский