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2. Exploring the impact of vibrational cavity coupling strength on ultrafast CN + $c$-C$_6$H$_{12}$ reaction dynamics

Author

Chen, Liying, Fidler, Ashley P., McKillop, Alexander M., and Weichman, Marissa L.

Subjects
Physics - Chemical Physics, Quantum Physics
Abstract

Molecular polaritons, hybrid light-matter states resulting from strong cavity coupling of optical transitions, may provide a new route to guide chemical reactions. However, demonstrations of cavity-modified reactivity in clean benchmark systems are still needed to clarify the mechanisms and scope of polariton chemistry. Here, we use transient absorption to observe the ultrafast dynamics of CN radicals interacting with a cyclohexane ($c$-C$_6$H$_{12}$) and chloroform (CHCl$_3$) solvent mixture under vibrational strong coupling of the brightest C$-$H stretching mode of $c$-C$_6$H$_{12}$. By modulating the $c$-C$_6$H$_{12}$:CHCl$_3$ ratio, we explore how solvent complexation and hydrogen (H)-abstraction processes proceed under collective cavity coupling strengths ranging from 55$-$85 cm$^{-1}$. Reaction rates remain unchanged for all extracavity, on resonance, and off-resonance cavity coupling conditions, regardless of coupling strength. These results suggest that insufficient vibrational cavity coupling strength may not be the determining factor for the negligible cavity effects observed previously in H-abstraction reactions of CN with CHCl$_3$.

Published
2023
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6. Ultrafast dynamics of CN radical reactions with chloroform solvent under vibrational strong coupling

Author

Fidler, Ashley P., Chen, Liying, McKillop, Alexander M., and Weichman, Marissa L.

Subjects
Physics - Chemical Physics, Physics - Optics
Abstract

Polariton chemistry may provide a new means to control molecular reactivity, permitting remote, reversible modification of reaction energetics, kinetics, and product yields. A considerable body of experimental and theoretical work has already demonstrated that strong coupling between a molecular vibrational mode and the confined electromagnetic field of an optical cavity can alter chemical reactivity without external illumination. However, the mechanisms underlying cavity-altered chemistry remain unclear in large part because the experimental systems examined previously are too complex for detailed analysis of their reaction dynamics. Here, we experimentally investigate photolysis-induced reactions of cyanide (CN) radicals with strongly-coupled chloroform (CHCl$_3$) solvent molecules and examine the intracavity rates of photofragment recombination, solvent complexation, and hydrogen abstraction. We use a microfluidic optical cavity fitted with dichroic mirrors to facilitate vibrational strong coupling (VSC) of the C-H stretching mode of CHCl$_3$ while simultaneously permitting optical access at visible wavelengths. Ultrafast transient absorption experiments performed with cavities tuned on- and off-resonance reveal that VSC of the CHCl$_3$ C-H stretching transition does not significantly modify any measured rate constants, including those associated with the hydrogen abstraction reaction. This work represents, to the best of our knowledge, the first experimental study of an elementary bimolecular reaction under VSC. We discuss how the conspicuous absence of cavity-altered effects in this system may provide insights into the mechanisms of modified ground state reactivity under VSC and help bridge the divide between experimental results and theoretical predictions in vibrational polariton chemistry.

Published
2023
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18. Exploring the impact of vibrational cavity coupling strength on ultrafast CN + c-C6H12 reaction dynamics

Author

Chen Liying, Fidler Ashley P., McKillop Alexander M., and Weichman Marissa L.

Subjects
polariton chemistry, vibrational strong coupling, hydrogen abstraction reactions, ultrafast transient absorption, Physics, QC1-999
Abstract

Molecular polaritons, hybrid light-matter states resulting from strong cavity coupling of optical transitions, may provide a new route to guide chemical reactions. However, demonstrations of cavity-modified reactivity in clean benchmark systems are still needed to clarify the mechanisms and scope of polariton chemistry. Here, we use transient absorption to observe the ultrafast dynamics of CN radicals interacting with a cyclohexane (c-C6H12) and chloroform (CHCl3) solvent mixture under vibrational strong coupling of a C–H stretching mode of c-C6H12. By modulating the c-C6H12:CHCl3 ratio, we explore how solvent complexation and hydrogen (H)-abstraction processes proceed under collective cavity coupling strengths ranging from 55 to 85 cm−1. Reaction rates remain unchanged for all extracavity, on-resonance, and off-resonance cavity coupling conditions, regardless of coupling strength. These results suggest that insufficient vibrational cavity coupling strength may not be the determining factor for the negligible cavity effects observed previously in H-abstraction reactions of CN with CHCl3.

Published
2024
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19. Differences in In Vitro Digestibility of Curcumin Nanoemulsions Stabilized by Whey Protein Isolate and Whey Protein Isolate-(–)-Epigallocatechin-3-gallate

Author

LI Yanxin, CHEN Liying, LI Yan, XIE Xin’an, LI Lu

Subjects
whey protein isolate-(-)-epigallocatechin-3-gallate grafts, nanoemulsion, in vitro digestion, free fatty acid release, Food processing and manufacture, TP368-456
Abstract

In this study, the release of free fat acids (FFA) from and the digestion characteristics of curcumin nanoemulsions constructed using whey protein isolate (WPI)-(-)-epigallocatechin-3-gallate (ECGG) graft copolymers with 3% and 4% grafting degrees as emulsifiers were investigated during in vitro simulated digestion and compared with those of curcumin nanoemulsions stabilized by WPI. It was found that binding to EGCG might cause the unfolding of WPI, and the interfacial film thickness of the WPI-EGCG stabilized emulsion increased by 31.6 nm compared with that of the WPI stabilized emulsion. The WPI-EGCG complex stabilized emulsion had a smaller particle size dispersion and average particle size than the WPI stabilized emulsion and was therefore more stable and superior in promoting lipid digestion. After 120 minutes of intestinal digestion, the final release rate of FFA from the nanoemulsion stabilized with 4% WPI-EGCG was 85.13%. Also, the graft treatment improved the bioaccessibility of curcumin encapsulated in the system.

Published
2024
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24. Research on prediction of support parameters for coal roadways

Author

CHEN Pan, MA Xinmin, XIANG Junjie, CHEN Liying, and LIANG Tinghao

Subjects
coal mine roadway, machine learning, anchor rod support parameters, oversampling of synthesized minority classes, genetic algorithm optimizing support vector machine, Mining engineering. Metallurgy, TN1-997
Abstract

Currently, algorithms such as support vector machine (SVM) and random forest (RF) are less applied in the field of coal mine roadway support. The paper studies the applicability of different machine learning models for support parameter design.Thus a higher performance model would be established to achieve reasonable and scientific design of anchor bolt support. Firstly, it is suggested to establish an intelligent prediction database for coal mine roadway support. Through on-site research, questionnaire survey, and literature search, the coal mine roadway samples are collected. The data is processed using methods such as filling in missing values, modifying outliers in box charts, and removing local abnormal factors to establish a coal roadway support database. The paper proposes a coal roadway support parameter prediction model based on synthetic minority oversampling technique (SMOTE) - genetic algorithm (GA) - SVM. The data in the database is divided into training and testing sets. The SMOTE technology is used to balance training samples, and improve the model's fitting capability for minority class samples. The training process uses GA to globally optimize the hyperparameters of SVM, further improving the overall performance of the model. The test results show that the classificaton precision of the SMOTE-GA-SVM model reaches 83.8%, which is 21.8% higher than the traditional SVM model. The machine learning methods such as SVM, artificial neural network (ANN), RF, AdaBoost (ADA), and naive Bayesian classifier (NBC) are introduced into the prediction of coal roadway anchor support parameters. The corresponding support parameter prediction models are established. The comparison results showed that the best to worst prediction models are ranked as SMOTE-GA-SVM, RF, GA-ANN, SVM, NBC, and ADA, with an average classificaton precision of 69.9%. The result verifies the feasibility of machine learning methods in predicting the parameters of coal roadway bolt support. The SMOTE-GA-SVM model is applied in Shanxi Huobaoganhe Coal Mine Co., Ltd., with a precision of 87.5% and strong applicability and reliability.

Published
2023
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