Computer aided recipe design: optimization of polydisperse chemical mixtures using molecular descriptors

A.P. MacKenzie; Jakob Schneider; Jan Meyer; Christoph Loschen

doi:10.1039/d3re00601h

January 1, 2024Reaction Chemistry & Engineering

Computer aided recipe design: optimization of polydisperse chemical mixtures using molecular descriptors

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Key Points

Develop an integrated computational framework to optimize polydisperse chemical formulations and accelerate raw material replacement.
Coupled kinetic Monte Carlo simulations with cheminformatics methodologies to model polydisperse mixture behaviors.
Employed molecular descriptors to guide the reverse engineering and property-targeted formulation of chemical mixtures.
Established a functional workflow for the inverse design of complex, polydisperse chemical formulations.
Demonstrated computational raw material substitution without requiring extensive empirical trial-and-error laboratory synthesis.

Implication

Computational modeling demonstrates accelerated raw material replacement in polydisperse chemical mixtures, suggesting efficient pathways for reverse formulation design.

Abstract

Computational approach for accelerated raw material replacement: reverse design of polydisperse chemical mixtures combining kinetic Monte Carlo and cheminformatics.

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Cite This Study

MacKenzie et al. (2024) studied this question.

synapsesocial.com/papers/6a9705ff7c15eaca0257958c https://doi.org/10.1039/d3re00601h

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Computer aided recipe design: optimization of polydisperse chemical mixtures using molecular descriptors

Key Points

Implication

Abstract

Discussion

Cite This Study

Computer aided recipe design: optimization of polydisperse chemical mixtures using molecular descriptors

Key Points

Implication

Abstract

Discussion

Cite This Study

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