Identifying Green Solvent Mixtures for Bioproduct Separation Using Bayesian Experimental Design DOI
Shiyi Qin, Surajudeen Omolabake,

Aminata Diaby

и другие.

ACS Sustainable Chemistry & Engineering, Год журнала: 2024, Номер 12(52), С. 18634 - 18647

Опубликована: Дек. 13, 2024

Liquid–liquid extraction (LLE) is a widely used technique for the separation and purification of liquid-phase products with applications in various industries, including pharmaceuticals, petrochemicals, renewable chemistry. A critical step design an LLE process selection appropriate solvents. This study presents new methodology identifying solvent mixtures bioproduct using Bayesian experimental (BED). Motivated by need environmentally friendly effective methods, we address challenge selecting systems that balance efficiency, selectivity, environmental impact while also tackling difficulty separating multiple bioproducts complex systems. Our approach specifically seeks to predict product partition coefficients (log10 Kp values) as thermodynamic parameters underlying selection. The iterative integrates optimization measurements guide leverages COSMO-RS simulations enhance high-throughput experimentation. Using lignin-derived aromatic via centrifugal chromatography (CPC) case study, show within seven iterations/cycles methodology, can identify green solvents align CPC principles. These results demonstrate efficacy BED framework optimizing separations, highlighting potential this method advance field chemistry contribute development sustainable industrial processes.

Язык: Английский

Self-Driving Laboratories for Chemistry and Materials Science DOI Creative Commons
Gary Tom, Stefan P. Schmid, Sterling G. Baird

и другие.

Chemical Reviews, Год журнала: 2024, Номер 124(16), С. 9633 - 9732

Опубликована: Авг. 13, 2024

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through automation experimental workflows, along with autonomous planning, SDLs hold potential to greatly accelerate research in chemistry and materials discovery. This review provides in-depth analysis state-of-the-art SDL technology, its applications across various disciplines, implications for industry. additionally overview enabling technologies SDLs, including their hardware, software, integration laboratory infrastructure. Most importantly, this explores diverse range domains where have made significant contributions, from drug discovery science genomics chemistry. We provide a comprehensive existing real-world examples different levels automation, challenges limitations associated each domain.

Язык: Английский

Процитировано

56
AI Approaches to Homogeneous Catalysis with Transition Metal Complexes DOI Creative Commons
Lucía Morán‐González, Arron L. Burnage, Ainara Nova

и другие.

ACS Catalysis, Год журнала: 2025, Номер unknown, С. 9089 - 9105

Опубликована: Май 14, 2025

Язык: Английский

Процитировано

0
Identifying Green Solvent Mixtures for Bioproduct Separation Using Bayesian Experimental Design DOI
Shiyi Qin, Surajudeen Omolabake,

Aminata Diaby

и другие.

ACS Sustainable Chemistry & Engineering, Год журнала: 2024, Номер 12(52), С. 18634 - 18647

Опубликована: Дек. 13, 2024

Liquid–liquid extraction (LLE) is a widely used technique for the separation and purification of liquid-phase products with applications in various industries, including pharmaceuticals, petrochemicals, renewable chemistry. A critical step design an LLE process selection appropriate solvents. This study presents new methodology identifying solvent mixtures bioproduct using Bayesian experimental (BED). Motivated by need environmentally friendly effective methods, we address challenge selecting systems that balance efficiency, selectivity, environmental impact while also tackling difficulty separating multiple bioproducts complex systems. Our approach specifically seeks to predict product partition coefficients (log10 Kp values) as thermodynamic parameters underlying selection. The iterative integrates optimization measurements guide leverages COSMO-RS simulations enhance high-throughput experimentation. Using lignin-derived aromatic via centrifugal chromatography (CPC) case study, show within seven iterations/cycles methodology, can identify green solvents align CPC principles. These results demonstrate efficacy BED framework optimizing separations, highlighting potential this method advance field chemistry contribute development sustainable industrial processes.

Язык: Английский

Процитировано

0