QM/MM Modeling of Vibrational Polariton Induced Energy Transfer and Chemical Dynamics

Li, Tao E.; Hammes‐Schiffer, Sharon

doi:10.1021/jacs.2c10170

Cited by 12 publications

(10 citation statements)

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“…Notably, only polaritons can modify the molecular energy exchange dynamics, as exciting dark modes failed to evoke changes (Figure c and d). Similar insights were garnered from QM-MM cavity simulations by Li and Hammes-Schiffer, confirming the role of polaritons and dark modes in reshaping energy transfer and molecular dynamics …”

Section: Ultrafast Dynamics Of Molecular Polariton Systems Via Cohere...supporting

confidence: 71%

Molecular Polaritons for Chemistry, Photonics and Quantum Technologies

Xiang,

Xiong

2024

Chem. Rev.

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Molecular polaritons are quasiparticles resulting from the hybridization between molecular and photonic modes. These composite entities, bearing characteristics inherited from both constituents, exhibit modified energy levels and wave functions, thereby capturing the attention of chemists in the past decade. The potential to modify chemical reactions has spurred many investigations, alongside efforts to enhance and manipulate optical responses for photonic and quantum applications. This Review centers on the experimental advances in this burgeoning field. Commencing with an introduction of the fundamentals, including theoretical foundations and various cavity architectures, we discuss outcomes of polariton-modified chemical reactions. Furthermore, we navigate through the ongoing debates and uncertainties surrounding the underpinning mechanism of this innovative method of controlling chemistry. Emphasis is placed on gaining a comprehensive understanding of the energy dynamics of molecular polaritons, in particular, vibrational molecular polaritons�a pivotal facet in steering chemical reactions. Additionally, we discuss the unique capability of coherent twodimensional spectroscopy to dissect polariton and dark mode dynamics, offering insights into the critical components within the cavity that alter chemical reactions. We further expand to the potential utility of molecular polaritons in quantum applications as well as precise manipulation of molecular and photonic polarizations, notably in the context of chiral phenomena. This discussion aspires to ignite deeper curiosity and engagement in revealing the physics underpinning polariton-modified molecular properties, and a broad fascination with harnessing photonic environments to control chemistry.

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Section: Ultrafast Dynamics Of Molecular Polariton Systems Via Cohere...supporting

confidence: 71%

Molecular Polaritons for Chemistry, Photonics and Quantum Technologies

Xiang,

Xiong

2024

Chem. Rev.

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“…Other driving forces, such as excitation to hot vibrational modes, could also play a role. This VSC-modified dynamics was just recently supported by a hybrid quantum-mechanical/molecular-mechanical cavity molecular dynamics scheme, which could provide critical mechanistic insights in the future. The reflectivity of distributed Bragg reflector (DBR) optics can depend on the polarizations of incoming beams, which may influence the anisotropy.…”

Section: Vibrational-polariton-modified Pseudorotation Dynamicsmentioning

confidence: 90%

Molecular Vibrational Polariton Dynamics: What Can Polaritons Do?

Xiong

2023

Acc. Chem. Res.

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Metrics & MoreArticle Recommendations CONSPECTUS: When molecular vibrational modes strongly couple to virtual states of photonic modes, new molecular vibrational polariton states are formed, along with a large population of dark reservoir modes. The polaritons are much like the bonding and antibonding molecular orbitals when atomic orbitals form molecular bonds, while the dark modes are like nonbonding orbitals. Because the polariton states are half-matter and half-light, whose energy is shifted from the parental states, polaritons are predicted to modify chemistry under thermally activated conditions, leading to an exciting and emerging field known as polariton chemistry that could potentially shift paradigms in chemistry. Despite several published results supporting this concept, the chemical physics and mechanism of polariton chemistry remain elusive. One reason for this challenge is that previous works cannot differentiate polaritons from dark modes. This limitation makes delineating the contributions to chemistry from polaritons and dark states difficult. However, this level of insight is critical for developing a solid mechanism for polariton chemistry to design and predict the outcome of strong coupling with any given reaction. My group addressed the challenge of differentiating the dynamics of polaritons and dark modes by ultrafast two-dimensional infrared (2D IR) spectroscopy. Specifically, (1) we found that polaritons can facilitate intra-and intermolecular vibrational energy transfer, opening a pathway to control vibrational energy flow in liquid-phase molecular systems, and (2) by studying a single-step isomerization event, we verified that indeed polaritons can modify chemical dynamics under strong coupling conditions, but in contrast, the dark modes behave like uncoupled molecules and do not change the dynamics. This finding confirmed the central concept of polariton chemistry: polaritons modify the potential energy landscape of reactions. The result also clarified the role of dark modes, which lays a critical foundation for designing cavities for future polariton chemistry. Aside from using 2D IR spectroscopy to study polariton chemistry, we also used the same technique to develop molecular polaritons into a potential quantum simulation platform. We demonstrated that polaritons have Rabi oscillations, and using a checkerboard cavity design, we showed that polaritons could have large nonlinearity across space. We further used the checkerboard polaritons to simulate coherence transfer and visualize it. A unidirectional coherence transfer was observed, indicating non-Hermitian dynamics. The highlighted efforts in this Account provide a solid understanding of the capability of polaritons for chemistry and quantum information science. I conclude this Account by discussing a few challenges for moving polariton chemistry toward being predictable and making the polariton quantum platform a complement to existing systems.

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“…While the number of atoms in the system that can be handled by MM can be as large as a million, the system suitable for QM and DFT may have only a few dozen atoms. Therefore, QM/MM methods have been developed to combine the advantages of MM and QM while taking into account the computing cost of QM and the size of most biological systems . In QM/MM methods, the active site is handled by QM, while the rest of the system is considered by MM.…”

Section: Perspectives For Molecular Sciencementioning

confidence: 99%

“…Therefore, QM/MM methods have been developed to combine the advantages of MM and QM while taking into account the computing cost of QM and the size of most biological systems. 506 In QM/MM methods, the active site is handled by QM, while the rest of the system is considered by MM.…”

Section: Physical Model-based Data Augmentationmentioning

confidence: 99%

Machine Learning Methods for Small Data Challenges in Molecular Science

et al. 2023

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Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and technical limitations in data acquisition. However, big data have been the focus for the past decade, small data and their challenges have received little attention, even though they are technically more severe in machine learning (ML) and deep learning (DL) studies. Overall, the small data challenge is often compounded by issues, such as data diversity, imputation, noise, imbalance, and high-dimensionality. Fortunately, the current big data era is characterized by technological breakthroughs in ML, DL, and artificial intelligence (AI), which enable data-driven scientific discovery, and many advanced ML and DL technologies developed for big data have inadvertently provided solutions for small data problems. As a result, significant progress has been made in ML and DL for small data challenges in the past decade. In this review, we summarize and analyze several emerging potential solutions to small data challenges in molecular science, including chemical and biological sciences. We review both basic machine learning algorithms, such as linear regression, logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), kernel learning (KL), random forest (RF), and gradient boosting trees (GBT), and more advanced techniques, including artificial neural network (ANN), convolutional neural network (CNN), U-Net, graph neural network (GNN), Generative Adversarial Network (GAN), long short-term memory (LSTM), autoencoder, transformer, transfer learning, active learning, graph-based semi-supervised learning, combining deep learning with traditional machine learning, and physical model-based data augmentation. We also briefly discuss the latest advances in these methods. Finally, we conclude the survey with a discussion of promising trends in small data challenges in molecular science.

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QM/MM Modeling of Vibrational Polariton Induced Energy Transfer and Chemical Dynamics

Cited by 12 publications

References 58 publications

Molecular Polaritons for Chemistry, Photonics and Quantum Technologies

Molecular Polaritons for Chemistry, Photonics and Quantum Technologies

Molecular Vibrational Polariton Dynamics: What Can Polaritons Do?

Machine Learning Methods for Small Data Challenges in Molecular Science

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