Analysis and Artificial Neural Network Prediction of Melting Properties and Ideal Mole fraction Solubility of Cocrystals-Reference-Cited by-同舟云学术

Analysis and Artificial Neural Network Prediction of Melting Properties and Ideal Mole fraction Solubility of Cocrystals

Published:2020-07-14 Issue:9 Volume:20 Page:5745-5759
ISSN:1528-7483
Container-title:Crystal Growth & Design
language:en
Short-container-title:Crystal Growth & Design

Author:

Gamidi Rama Krishna¹²^ORCID,Rasmuson Åke C.¹^ORCID

Affiliation:

1. Department of Chemical and Environmental Science, Synthesis and Solid State Pharmaceutical Centre, Bernal Institute, University of Limerick, Limerick, Ireland

2. Organic Chemistry Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune, Maharashtra 411 008, India

Funder

Science and Engineering Research Board

Science Foundation Ireland

European Regional Development Fund

Publisher

American Chemical Society (ACS)

Subject

Condensed Matter Physics,General Materials Science,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.cgd.0c00182

Reference46 articles.

1. Relative Enthalpy of Formation for Co-Crystals of Small Organic Molecules

2. Towards ab initio screening of co-crystal formation through lattice energy calculations and crystal structure prediction of nicotinamide, isonicotinamide, picolinamide and paracetamol multi-component crystals

3. Evaluating the Energetic Driving Force for Cocrystal Formation

4. Reversibility of Enantiotropically Related Polymorphic Transformations from a Practical Viewpoint: Thermal Analysis of Kinetically Reversible/Irreversible Polymorphic Transformations

5. Challenges and Strategies in Thermal Processing of Amorphous Solid Dispersions: A Review

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