On January 4, 2017, Gamidi, Rama Krishna; Rasmuson, Ake. C. published an article.Category: chlorides-buliding-blocks The title of the article was Estimation of Melting Temperature of Molecular Cocrystals Using Artificial Neural Network Model. And the article contained the following:
A Quant. Structure-activity Relationship (QSAR) model has been constructed by Artificial Neural Networks (ANNs) for estimation of melting temperature (Tm) of mol. cocrystals (CCs). Based on a literature anal. using Scifinder and Cambridge Structural Database (CSD) softwares, a database has been created over CCs for four Active Pharmaceutical Ingredients (APIs), namely, i.e. caffeine (CAF), theophylline (THP), nicotinamide (NA) and isonicotinamide (INA). In total, of 61 CCs were included: 14-CAF, 9-THP, 29-INA and 9-NA. A good correlation was obtained with ANNs to quantify the Tm of the CCs with respect to various coformers (COF). The training process was completed with an average relative error of 2.38%, whereas the relative error for the validation set was 2.89%. The experimental process involved the reaction of 2-Chloro-4-nitrobenzoic acid(cas: 99-60-5).Category: chlorides-buliding-blocks
The Article related to estimation melting temperature mol cocrystal artificial neural network model, Physical Organic Chemistry: Theoretical Organic Chemical Concepts, Including Quantum and Molecular Mechanical Studies and other aspects.Category: chlorides-buliding-blocks
Referemce:
Chloride – Wikipedia,
Chlorides – an overview | ScienceDirect Topics