Machine Learning for Electronically Excited States of Molecules

Chemical Reviews, Journal Year: 2020, Volume and Issue: 121(16), P. 9873 - 9926

Published: Nov. 19, 2020

Electronically excited states of molecules are at the heart photochemistry, photophysics, as well photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculations, which computationally expensive. In this review, we focus on not only how machine learning is employed to speed up such excited-state simulations but branch artificial intelligence can be used advance exciting research field all its aspects. Discussed applications for include dynamics simulations, static calculations absorption spectra, many others. order put these studies into context, discuss promises pitfalls involved techniques. Since latter mostly based chemistry provide short introduction electronic structure methods approaches nonadiabatic describe tricks problems when using them molecules.

Language: Английский

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Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(12), P. 10970 - 11021

Published: May 16, 2022

Rechargeable batteries have become indispensable implements in our daily life and are considered a promising technology to construct sustainable energy systems the future. The liquid electrolyte is one of most important parts battery extremely critical stabilizing electrode–electrolyte interfaces constructing safe long-life-span batteries. Tremendous efforts been devoted developing new solvents, salts, additives, recipes, where molecular dynamics (MD) simulations play an increasingly role exploring structures, physicochemical properties such as ionic conductivity, interfacial reaction mechanisms. This review affords overview applying MD study electrolytes for rechargeable First, fundamentals recent theoretical progress three-class summarized, including classical, ab initio, machine-learning (section 2). Next, application exploration electrolytes, probing bulk structures 3), deriving macroscopic conductivity dielectric constant 4), revealing mechanisms 5), sequentially presented. Finally, general conclusion insightful perspective on current challenges future directions provided. Machine-learning technologies highlighted figure out these challenging issues facing research promote rational design advanced next-generation

Language: Английский

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Molecular mechanism of aggregation‐induced emission

Aggregate, Journal Year: 2021, Volume and Issue: 2(5)

Published: June 3, 2021

Abstract Deep understanding of the inherent luminescence mechanism is essential for development aggregation‐induced emission (AIE) materials and applications. We first note that intermolecular excitonic coupling much weaker in strength than intramolecular electron‐vibration a majority newly termed AIEgens, which leads to peak position insensitive coupling, hence conventional model J‐aggregation cannot effectively explain their AIE phenomena. Then, using multiscale computational approach coupled with our self‐developed thermal vibration correlation function rate formalism transition‐state theory, we quantitatively investigate aggregation effect on both radiative nonradiative decays molecular excited states. For decay processes, propose lowest state could convert from transition dipole‐forbidden “dark” dipole‐allowed “bright” upon aggregation. radiationless demonstrate blockage via relaxation (BNR‐VR) harmonic region or removal isomerization (RNR‐ISO) minimum energy crossing point (RNR‐MECP) beyond variety aggregates. Our theoretical work not only justifies plethora experimental results but also makes reliable predictions design can be experimentally verified. Looking forward, believe this review will benefit deep about universality phenomenon further extending scope systems novel

Language: Английский

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Polarizable embedding QM/MM: the future gold standard for complex (bio)systems?

Physical Chemistry Chemical Physics, Journal Year: 2020, Volume and Issue: 22(26), P. 14433 - 14448

Published: Jan. 1, 2020

We provide a perspective of the induced dipole formulation polarizable QM/MM, showing how efficient implementations will enable their application to modeling dynamics, spectroscopy, and reactivity in complex biosystems.

Language: Английский

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Molecular excited states through a machine learning lens

Nature Reviews Chemistry, Journal Year: 2021, Volume and Issue: 5(6), P. 388 - 405

Published: May 20, 2021

Language: Английский

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Rational Design of Photocatalysts for Controlled Polymerization: Effect of Structures on Photocatalytic Activities

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(6), P. 5476 - 5518

Published: Jan. 4, 2022

Over the past decade, use of photocatalysts (PCs) in controlled polymerization has brought new opportunities sophisticated macromolecular synthesis. However, selection PCs these systems been typically based on laborious trial-and-error strategies. To tackle this limitation, computer-guided rational design knowledge structure-property-performance relationships emerged. These strategies provide rapid and economic methodologies for tuning performance functionality a system, thus providing further polymer science. This review provides an overview employed photocontrolled summarizes their progression from early to current state-of-the-art. Background theories electronic transitions are also introduced establish perspective quantum chemistry. Typical examples each type structure-property then presented enlighten future polymerization.

Language: Английский

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Theoretical Advances in Polariton Chemistry and Molecular Cavity Quantum Electrodynamics

Chemical Reviews, Journal Year: 2023, Volume and Issue: 123(16), P. 9786 - 9879

Published: Aug. 8, 2023

When molecules are coupled to an optical cavity, new light-matter hybrid states, so-called polaritons, formed due quantum interactions. With the experimental demonstrations of modifying chemical reactivities by forming polaritons under strong interactions, theorists have been encouraged develop methods simulate these systems and discover strategies tune control reactions. This review summarizes some exciting theoretical advances in polariton chemistry, ranging from fundamental framework computational techniques applications spanning photochemistry vibrational coupling. Even though theory interactions goes back midtwentieth century, gaps knowledge molecular electrodynamics (QED) only recently filled. We recent made resolving gauge ambiguities, correct form different QED Hamiltonians gauges, their connections various optics models. Then, we developed ab initio approaches which can accurately describe states a realistic molecule-cavity system. then discuss using method advancements. advancements where cavity is resonant electronic transitions nonadiabatic excited state dynamics enable photochemical reactivities. resonance tuned vibrations instead, ground-state reaction modifications demonstrated experimentally, its mechanistic principle remains unclear. present progress this mystery. Finally, understanding collective coupling regime between light matter, many collectively couple single mode or modes. also lay out current challenges explain observed results. hope that will serve as useful document for anyone who wants become familiar with context chemistry thus significantly benefit entire community.

Language: Английский

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Electronic Structure Methods for the Description of Nonadiabatic Effects and Conical Intersections

Chemical Reviews, Journal Year: 2021, Volume and Issue: 121(15), P. 9407 - 9449

Published: June 22, 2021

Nonadiabatic effects are ubiquitous in photophysics and photochemistry, therefore, many theoretical developments have been made to properly describe them. Conical intersections central nonadiabatic processes, as they promote efficient ultrafast transitions between electronic states. A proper description requires structure specifically methods that conical states coupling terms. This review focuses on the aspects of processes. We discuss requirements couplings, how most common excited state perform describing these effects, what recent expanding methodology implementing couplings.

Language: Английский

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Carbon Nanodots from an In Silico Perspective

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(16), P. 13709 - 13799

Published: Aug. 10, 2022

Carbon nanodots (CNDs) are the latest and most shining rising stars among photoluminescent (PL) nanomaterials. These carbon-based surface-passivated nanostructures compete with other related PL materials, including traditional semiconductor quantum dots organic dyes, a long list of benefits emerging applications. Advantages CNDs include tunable inherent optical properties high photostability, rich possibilities for surface functionalization doping, dispersibility, low toxicity, viable synthesis (top-down bottom-up) from materials. can be applied to biomedicine imaging sensing, drug-delivery, photodynamic therapy, photocatalysis but also energy harvesting in solar cells as LEDs. More applications reported continuously, making this already research field its own. Understanding requires one go levels electrons, atoms, molecules, at different scales using modern molecular modeling correlate it tightly experiments. This review highlights silico techniques studies, chemistry mesoscale, particular reference carbon nanodots, carbonaceous nanoparticles whose structural photophysical not fully elucidated. The role experimental investigation is presented. Hereby, we hope encourage reader investigate apply virtual obtain further insights needed customize these amazing systems novel prospective

Language: Английский

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Molecular dynamics-to-machine learning for deep eutectics in energy storages

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 212, P. 115358 - 115358

Published: Jan. 20, 2025

Language: Английский

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