This paper expands our work predicting Process Mass Intensity (PMI), as a methodology for exploring the potential efficiency of proposed synthetic routes. In the present work, we integrate a method for predicting the PMI contributions of high complexity reagents, needed to enable certain transformations. We focus on ligands for metal catalyzed reactions - and develop an approach for predicting which ligands may function in CN couplings - as a proof of concept. We leverage this to enable the integration of the PMI contribution of the ligands into a predictions of a routes efficiency, enabling an understanding of the holistic impact of a route decision.
This report describes mathematical relationships between step and cumulative process mass intensitie...
The synthesis of molecules with desired properties is an important part of some areas of science and...
The application of modern machine learning to challenges in atomistic simulation is gaining attracti...
ChemPager is a freely available data analysis tool for analyzing, comparing and improving synthetic ...
Designing efficient and green approaches to complex molecules is a challenge faced by any organizati...
Herein we describe a green-by-design approach to route selection and development, assisted by predic...
Process mass intensity (PMI) is a key mass-based metric to evaluate the green credentials of an indi...
Computational prediction of reaction outcomes and optimum synthetic routes was a two-day meeting and...
Numerous different algorithms have been developed over the last few years which are capable of gener...
This thesis explores the use of mass-based reaction metrics to analyses a chemical process and ident...
Success of newly discovered chemistry in academia is often scored in terms of its novelty and level ...
From Mechanistic Investigation to Quantitative Prediction: Kinetics of Homogeneous Transition Metal-...
Organometallic catalysis facilitates the synthesis of diverse products ranging from polyolefin mater...
Numerous different algorithms have been developed over the last few years which are capable of gener...
Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components...
This report describes mathematical relationships between step and cumulative process mass intensitie...
The synthesis of molecules with desired properties is an important part of some areas of science and...
The application of modern machine learning to challenges in atomistic simulation is gaining attracti...
ChemPager is a freely available data analysis tool for analyzing, comparing and improving synthetic ...
Designing efficient and green approaches to complex molecules is a challenge faced by any organizati...
Herein we describe a green-by-design approach to route selection and development, assisted by predic...
Process mass intensity (PMI) is a key mass-based metric to evaluate the green credentials of an indi...
Computational prediction of reaction outcomes and optimum synthetic routes was a two-day meeting and...
Numerous different algorithms have been developed over the last few years which are capable of gener...
This thesis explores the use of mass-based reaction metrics to analyses a chemical process and ident...
Success of newly discovered chemistry in academia is often scored in terms of its novelty and level ...
From Mechanistic Investigation to Quantitative Prediction: Kinetics of Homogeneous Transition Metal-...
Organometallic catalysis facilitates the synthesis of diverse products ranging from polyolefin mater...
Numerous different algorithms have been developed over the last few years which are capable of gener...
Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components...
This report describes mathematical relationships between step and cumulative process mass intensitie...
The synthesis of molecules with desired properties is an important part of some areas of science and...
The application of modern machine learning to challenges in atomistic simulation is gaining attracti...