Computer Aided Molecular Design of Green Solvents for the Hydroformylation of Long-Chain Olefines

Keßler, Tobias; Kunde, Christian; Linke, Steffen; McBride, Kevin; Sundmacher, Kai; Kienle, Achim

doi:10.1016/b978-0-12-823377-1.50125-7

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…In contrast to that, this work also aims at identifying new ecologically benign solvent candidates not yet included in the databases with even better performance. A hierarchical computer-75 aided molecular design approach for the considered process was presented in (Keßler et al, 2020), where the search-space was reduced to a neighborhood of DMF, defined by the Hansen solubility parameters. In this work, the search-space reduction is done using a computational-quantum-chemistrybased approach, and the search-space is limited to a neighborhood of the 80 candidates identified in (Linke et al, 2020).…”

Section: Molecular Targeting Approaches Leave the Molecule Parameters In Physically-mentioning

confidence: 99%

Integrated computer-aided molecular and process design: Green solvents for the hydroformylation of long-chain olefines

Keßler

Kunde

Linke

et al. 2022

Chemical Engineering Science

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Section: Molecular Targeting Approaches Leave the Molecule Parameters In Physically-mentioning

confidence: 99%

Integrated computer-aided molecular and process design: Green solvents for the hydroformylation of long-chain olefines

Keßler

Kunde

Linke

et al. 2022

Chemical Engineering Science

Self Cite

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“…Thus, researchers apply the models but find ways to account for the prediction errors by, for example, relaxing the property constraints, running a sensitivity, uncertainty, or reliability analysis. The most common indices incorporated into CAMD are health, safety, and environmental indicators, − computed using such properties like acute oral toxicity and permissible exposure limits, flammability and explosiveness, and aquatic toxicity and bioconcentration, respectively. A limited number of studies integrated also LCA indices.…”

Section: Introductionmentioning

confidence: 99%

Prior Knowledge for Predictive Modeling: The Case of Acute Aquatic Toxicity

Shavalieva

Papadokonstantakis

Peters

2022

J. Chem. Inf. Model.

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Early assessment of the potential impact of chemicals on health and the environment requires toxicological properties of the molecules. Predictive modeling is often used to estimate the property values in silico from pre-existing experimental data, which is often scarce and uncertain. One of the ways to advance the predictive modeling procedure might be the use of knowledge existing in the field. Scientific publications contain a vast amount of knowledge. However, the amount of manual work required to process the enormous volumes of information gathered in scientific articles might hinder its utilization. This work explores the opportunity of semiautomated knowledge extraction from scientific papers and investigates a few potential ways of its use for predictive modeling. The knowledge extraction and predictive modeling are applied to the field of acute aquatic toxicity. Acute aquatic toxicity is an important parameter of the safety assessment of chemicals. The extensive amount of diverse information existing in the field makes acute aquatic toxicity an attractive area for investigation of knowledge use for predictive modeling. The work demonstrates that the knowledge collection and classification procedure could be useful in hybrid modeling studies concerning the model and predictor selection, addressing data gaps, and evaluation of models’ performance.

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Computer Aided Molecular Design of Green Solvents for the Hydroformylation of Long-Chain Olefines

Cited by 2 publications

References 10 publications

Integrated computer-aided molecular and process design: Green solvents for the hydroformylation of long-chain olefines

Integrated computer-aided molecular and process design: Green solvents for the hydroformylation of long-chain olefines

Prior Knowledge for Predictive Modeling: The Case of Acute Aquatic Toxicity

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