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1.
J Chem Inf Model ; 63(15): 4560-4573, 2023 08 14.
Artículo en Inglés | MEDLINE | ID: mdl-37432764

RESUMEN

The skew and shape of the molecular weight distribution (MWD) of polymers have a significant impact on polymer physical properties. Standard summary metrics statistically derived from the MWD only provide an incomplete picture of the polymer MWD. Machine learning (ML) methods coupled with high-throughput experimentation (HTE) could potentially allow for the prediction of the entire polymer MWD without information loss. In our work, we demonstrate a computer-controlled HTE platform that is able to run up to 8 unique variable conditions in parallel for the free radical polymerization of styrene. The segmented-flow HTE system was equipped with an inline Raman spectrometer and offline size exclusion chromatography (SEC) to obtain time-dependent conversion and MWD, respectively. Using ML forward models, we first predict monomer conversion, intrinsically learning varying polymerization kinetics that change for each experimental condition. In addition, we predict entire MWDs including the skew and shape as well as SHAP analysis to interpret the dependence on reagent concentrations and reaction time. We then used a transfer learning approach to use the data from our high-throughput flow reactor to predict batch polymerization MWDs with only three additional data points. Overall, we demonstrate that the combination of HTE and ML provides a high level of predictive accuracy in determining polymerization outcomes. Transfer learning can allow exploration outside existing parameter spaces efficiently, providing polymer chemists with the ability to target the synthesis of polymers with desired properties.


Asunto(s)
Polímeros , Peso Molecular , Polimerizacion , Polímeros/química
2.
Angew Chem Int Ed Engl ; 58(36): 12580-12584, 2019 Sep 02.
Artículo en Inglés | MEDLINE | ID: mdl-31310447

RESUMEN

Chlorosilanes are versatile reagents in organic synthesis and material science. A mild pathway is now reported for the quantitative conversion of hydrosilanes to silyl chlorides under visible-light irradiation using neutral eosin Y as a hydrogen-atom-transfer photocatalyst and dichloromethane as a chlorinating agent. Stepwise chlorination of di- and trihydrosilanes was achieved in a highly selective fashion assisted by continuous-flow micro-tubing reactors. The ability to access silyl radicals using photocatalytic Si-H activation promoted by eosin Y offers new perspectives for the synthesis of valuable silicon reagents in a convenient and green manner.

3.
Angew Chem Int Ed Engl ; 57(28): 8514-8518, 2018 07 09.
Artículo en Inglés | MEDLINE | ID: mdl-29718584

RESUMEN

Eosin Y, a well-known economical alternative to metal catalysts in visible-light-driven single-electron transfer-based organic transformations, can behave as an effective direct hydrogen-atom transfer catalyst for C-H activation. Using the alkylation of C-H bonds with electron-deficient alkenes as a model study revealed an extremely broad substrate scope, enabling easy access to a variety of important synthons. This eosin Y-based photocatalytic hydrogen-atom transfer strategy is promising for diverse functionalization of a wide range of native C-H bonds in a green and sustainable manner.

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