-
Notifications
You must be signed in to change notification settings - Fork 0
/
CITATION.cff
53 lines (52 loc) · 2.01 KB
/
CITATION.cff
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: >-
Machine Learning Approach for the Prediction of Eutectic
Temperatures for Metal-Free Deep Eutectic Solvents
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Anastasia K.
family-names: Lavrinenko
orcid: 'https://orcid.org/0000-0001-9863-8325'
- given-names: Ivan Yu.
family-names: Chernyshov
orcid: 'https://orcid.org/0000-0002-4452-2025'
- given-names: Evgeny A.
family-names: Pidko
orcid: 'https://orcid.org/0000-0001-9242-9901'
identifiers:
- type: doi
value: 10.1021/acssuschemeng.3c05207
repository-code: 'https://github.com/AstyLavrinenko/Eutectic-prediction'
abstract: >-
Deep eutectic solvents (DESs) represent an
environmental-friendly alternative to conventional organic
solvents. Their liquid range determines the areas of
application and therefore the prediction of the
solid-liquid equilibrium (SLE) diagrams is essential for
the development of new DESs. Such predictions are not yet
possible using the current state-of-the-art computational
models. Herein we present an alternative model based on
support vector regression integrating experimental data,
COSMO-RS simulations and cheminformatic descriptors for
computing the melting points of DESs and predicting SLEs.
The model was developed based on the manually collected
database of 1648 mixture melting temperatures for 237
experimentally described DESs and its accuracy was
demonstrated by 5-fold cross-validation (R2 ~ 0.8). The
presented methodology holds promise as a basis for the
automated high-throughput screening of molecular
combinations in the search for new DESs compositions with
pre-defined characteristics.
keywords:
- deep eutectic solvents
- COSMO-RS
- machine learning
- solid-liquid equilibrium
- melting point prediction
license: MIT
date-released: '2023-02-01'