Communications Chemistry,
Journal Year:
2024,
Volume and Issue:
7(1)
Published: Nov. 1, 2024
The
reproducibility
of
chemical
reactions,
when
obtaining
protocols
from
literature
or
databases,
is
highly
challenging
for
academicians,
industry
professionals
and
even
now
the
machine
learning
process.
To
synthesize
organic
molecule
under
photochemical
condition,
several
years
reaction
optimization,
skilled
manpower,
long
time
etc.
are
needed,
resulting
in
non-affordability
slow
down
research
development.
Herein,
we
have
introduced
DigiChemTree
backed
with
artificial
intelligence
to
auto-optimize
parameter
synthesizing
on
demand
library
molecules
fast
manner.
Newly,
auto-generated
digital
code
was
further
tested
late
stage
functionalization
various
active
pharmaceutical
ingredient.
Chemical Communications,
Journal Year:
2024,
Volume and Issue:
60(48), P. 6154 - 6157
Published: Jan. 1, 2024
An
electrochemical
three-component
reaction
involving
elemental
sulfur
is
disclosed
for
achieving
a
metal-free,
oxidant-free
synthesis
of
thioesters
in
high
atom-economical,
step-economical
and
chemoselective
manner.
Organic & Biomolecular Chemistry,
Journal Year:
2024,
Volume and Issue:
22(33), P. 6708 - 6712
Published: Jan. 1, 2024
An
efficient
method
for
the
construction
of
an
array
α-ketoamides
has
been
described
from
readily
available
O
-benzoyl
hydroxylamines
and
diazo
compounds
as
starting
materials
by
combined
use
CuI
a
catalyst
H
2
oxygen
source.
Organic Chemistry Frontiers,
Journal Year:
2024,
Volume and Issue:
11(19), P. 5502 - 5510
Published: Jan. 1, 2024
A
visible
light-induced
di/trifunctionalization
of
diazo
compounds
with
electron-rich
arenes
or
alkenes
has
been
developed.
This
provides
a
new
strategy
for
the
synthesis
α,α-diaryl-
and
α,α,α-triaryl-carbonyl
compounds,
1,4-dienes
indolizines.
Communications Chemistry,
Journal Year:
2024,
Volume and Issue:
7(1)
Published: Nov. 1, 2024
The
reproducibility
of
chemical
reactions,
when
obtaining
protocols
from
literature
or
databases,
is
highly
challenging
for
academicians,
industry
professionals
and
even
now
the
machine
learning
process.
To
synthesize
organic
molecule
under
photochemical
condition,
several
years
reaction
optimization,
skilled
manpower,
long
time
etc.
are
needed,
resulting
in
non-affordability
slow
down
research
development.
Herein,
we
have
introduced
DigiChemTree
backed
with
artificial
intelligence
to
auto-optimize
parameter
synthesizing
on
demand
library
molecules
fast
manner.
Newly,
auto-generated
digital
code
was
further
tested
late
stage
functionalization
various
active
pharmaceutical
ingredient.
