Applications of artificial intelligence and machine learning algorithms to crystallization

C Xiouras, F Cameli, GL Quillo… - Chemical …, 2022 - ACS Publications
Artificial intelligence and specifically machine learning applications are nowadays used in a
variety of scientific applications and cutting-edge technologies, where they have a …

Solubility, Extraction, and nanoparticles production in supercritical carbon dioxide: A mini‐review

G Sodeifian, MMB Usefi - ChemBioEng Reviews, 2023 - Wiley Online Library
Supercritical carbon dioxide (SC‐CO2) is CO2 that is stored beyond its critical point of 7.4
MPa and 31.1° C. Given the request for consumption of a green solvent for the environment …

[HTML][HTML] Challenges and opportunities in modelling wet granulation in pharmaceutical industry–a critical review

M Singh, S Shirazian, V Ranade, GM Walker… - Powder Technology, 2022 - Elsevier
Wet granulation is a key step in the pharmaceutical manufacturing of solid-dosage forms.
Wet granulation is used in pharmaceutical production to enhance formulation qualities such …

Application of artificial neural networks in the process analytical technology of pharmaceutical manufacturing—a review

B Nagy, DL Galata, A Farkas, ZK Nagy - The AAPS Journal, 2022 - Springer
Industry 4.0 has started to transform the manufacturing industries by embracing
digitalization, automation, and big data, aiming for interconnected systems, autonomous …

Challenges and opportunities concerning numerical solutions for population balances: a critical review

M Singh, V Ranade, O Shardt… - Journal of Physics A …, 2022 - iopscience.iop.org
Population balance models are tools for the study of dispersed systems, such as granular
materials, polymers, colloids and aerosols. They are applied with increasing frequency …

Computational prediction of drug solubility in supercritical carbon dioxide: Thermodynamic and artificial intelligence modeling

HC Nguyen, F Alamray, M Kamal, T Diana… - Journal of Molecular …, 2022 - Elsevier
In this study, machine learning (ML) computations were carried out for description of drug
solubility in supercritical carbon dioxide. Supercritical solvent has been used in this work …

[HTML][HTML] Machine learning method for simulation of adsorption separation: comparisons of model's performance in predicting equilibrium concentrations

G Yin, FJI Alazzawi, S Mironov, F Reegu… - Arabian Journal of …, 2022 - Elsevier
In this work, we implemented different models for predicting adsorption separation of a dye
from aqueous solution using porous materials. The equilibrium data of solute concentrations …

Machine learning based simulation of an anti-cancer drug (busulfan) solubility in supercritical carbon dioxide: ANFIS model and experimental validation

H Zhu, L Zhu, Z Sun, A Khan - Journal of Molecular Liquids, 2021 - Elsevier
In this work, a novel machine learning method (MLM) was developed based on Neuro fuzzy
system, ie, ANFIS (Adaptive neuro fuzzy inference system). This neuro fuzzy algorithm was …

[HTML][HTML] Multiple machine learning models for prediction of CO2 solubility in potassium and sodium based amino acid salt solutions

G Yin, FJI Alazzawi, D Bokov, HA Marhoon… - Arabian Journal of …, 2022 - Elsevier
In this work, we developed artificial intelligence-based models for prediction and correlation
of CO 2 solubility in amino acid solutions for the purpose of CO 2 capture. The models were …

Application of lignin in controlled release: development of predictive model based on artificial neural network for API release

M Pishnamazi, HY Ismail, S Shirazian, J Iqbal… - Cellulose, 2019 - Springer
Predictive models for simulation of drug release from tablets containing lignin as excipient
were developed in this work. Two predictive models including Artificial Neural Network …