Molecular Photochemistry: Recent Developments in Theory

Understanding the Photoprocesses in Biological Systems: Need for Accurate Multireference Treatment

Light-matter interaction is crucial to life itself and revolves around many of the central processes in biology. The need for understanding these photochemical and photophysical processes cannot be overemphasized. Interaction of light with biological systems starts with the absorption of light and subsequent phenomena that occur in the excited states of the system. However, excited states are typically difficult to understand within the mean field approximation of quantum chemical methods. Therefore, suitable multireference methods and methodologies have been developed to understand these phenomena. In this Perspective, we will describe a few methods and methodologies suitable for these descriptions and discuss some persisting difficulties.

MLatom Software Ecosystem for Surface Hopping Dynamics in Python with Quantum Mechanical and Machine Learning Methods

We present an open-source MLatom@XACS software ecosystem for on-the-fly surface hopping nonadiabatic dynamics based on the Landau-Zener-Belyaev-Lebedev algorithm. The dynamics can be performed via Python API with a wide range of quantum mechanical (QM) and machine learning (ML) methods, including ab initio QM (CASSCF and ADC(2)), semiempirical QM methods (e.g., AM1, PM3, OMx, and ODMx), and many types of ML potentials (e.g., KREG, ANI, and MACE). Combinations of QM and ML methods can also be used. While the user can build their own combinations, we provide AIQM1, which is based on Δ-learning and can be used out-of-the-box. We showcase how AIQM1 reproduces the isomerization quantum yield of trans-azobenzene at a low cost. We provide example scripts that, in dozens of lines, enable the user to obtain the final population plots by simply providing the initial geometry of a molecule. Thus, those scripts perform geometry optimization, normal mode calculations, initial condition sampling, parallel trajectories propagation, population analysis, and final result plotting. Given the capabilities of MLatom to be used for training different ML models, this ecosystem can be seamlessly integrated into the protocols building ML models for nonadiabatic dynamics. In the future, a deeper and more efficient integration of MLatom with Newton-X will enable a vast range of functionalities for surface hopping dynamics, such as fewest-switches surface hopping, to facilitate similar workflows via the Python API.

The development of the QM/MM interface and its application for the on-the-fly QM/MM nonadiabatic dynamics in JADE package: Theory, implementation, and applications

Understanding the nonadiabatic dynamics of complex systems is a challenging task in computational photochemistry. Herein, we present an efficient and user-friendly quantum mechanics/molecular mechanics (QM/MM) interface to run on-the-fly nonadiabatic dynamics. Currently, this interface consists of an independent set of codes designed for general-purpose use. Herein, we demonstrate the ability and feasibility of the QM/MM interface by integrating it with our long-term developed JADE package. Tailored to handle nonadiabatic processes in various complex systems, especially condensed phases and protein environments, we delve into the theories, implementations, and applications of on-the-fly QM/MM nonadiabatic dynamics. The QM/MM approach is established within the framework of the additive QM/MM scheme, employing electrostatic embedding, link-atom inclusion, and charge-redistribution schemes to treat the QM/MM boundary. Trajectory surface-hopping dynamics are facilitated using the fewest switches algorithm, encompassing classical and quantum treatments for nuclear and electronic motions, respectively. Finally, we report simulations of nonadiabatic dynamics for two typical systems: azomethane in water and the retinal chromophore PSB3 in a protein environment. Our results not only illustrate the power of the QM/MM program but also reveal the important roles of environmental factors in nonadiabatic processes.

Generalized Semiclassical Ehrenfest Method: A Route to Wave Function-Free Photochemistry and Nonadiabatic Dynamics with Only Potential Energies and Gradients

We reconsider recent methods by which direct dynamics calculations of electronically nonadiabatic processes can be carried out while requiring only adiabatic potential energies and their gradients. We show that these methods can be understood in terms of a new generalization of the well-known semiclassical Ehrenfest method. This is convenient because it eliminates the need to evaluate electronic wave functions and their matrix elements along the mixed quantum-classical trajectories. The new approximations and procedures enabling this advance are the curvature-driven approximation to the time-derivative coupling, the generalized semiclassical Ehrenfest method, and a new gradient correction scheme called the time-derivative matrix (TDM) scheme. When spin-orbit coupling is present, one can carry out dynamics calculations in the fully adiabatic basis using potential energies and gradients calculated without spin-orbit coupling plus the spin-orbit coupling matrix elements. Even when spin-orbit coupling is neglected, the method is useful because it allows calculations by electronic structure methods for which nonadiabatic coupling vectors are unavailable. In order to place the new considerations in context, the article starts out with a review of background material on trajectory surface hopping, the semiclassical Ehrenfest scheme, and methods for incorporating decoherence. We consider both internal conversion and intersystem crossing. We also review several examples from our group of successful applications of the curvature-driven approximation.

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

Analytic Nuclear Gradients for Complete Active Space Linearized Pair-Density Functional Theory

Accurately modeling photochemical reactions is difficult due to the presence of conical intersections and locally avoided crossings, as well as the inherently multiconfigurational character of excited states. As such, one needs a multistate method that incorporates state interaction in order to accurately model the potential energy surface at all nuclear coordinates. The recently developed linearized pair-density functional theory (L-PDFT) is a multistate extension of multiconfiguration PDFT, and it has been shown to be a cost-effective post-MCSCF method (as compared to more traditional and expensive multireference many-body perturbation methods or multireference configuration interaction methods) that can accurately model potential energy surfaces in regions of strong nuclear-electronic coupling in addition to accurately predicting Franck-Condon vertical excitations. In this paper, we report the derivation of analytic gradients for L-PDFT and their implementation in the PySCF-forge software, and we illustrate the utility of these gradients for predicting ground- and excited-state equilibrium geometries and adiabatic excitation energies for formaldehyde, s-trans-butadiene, phenol, and cytosine.

Ultrafast Excited-State Nonadiabatic Dynamics in Pt(II) Donor-Bridge-Acceptor Assemblies: A Quantum Approach for Optical Control

The ultrafast nonadiabatic excited state dynamics of (PTZ-N-benzyl-acetylide) (trans-bis-trimethylphosphine) Pt(II) (acetylide-NDI-bis-methyl) 1, representative of a series of Pt(II) donor-bridge-acceptor assemblies experimentally studied by the Weinstein group, University of Sheffield, is investigated by means of wavepacket propagations based on the multiconfiguration time-dependent Hartree (MCTDH) method. On the basis of electronic structure data obtained at the time-dependent density functional theory (TD-DFT) level, the subpicosecond decay is simulated by solving an 11 electronic states multimode problem, up to 18 vibrational normal modes, including both spin-orbit coupling (SOC) and vibronic coupling. A careful analysis of the results, within the diabatic representation, provides the key features of the spin-vibronic mechanism at work in this complex, distinguishing between the spin-orbit and vibronically activated ultrafast processes within the excited states manifold. The knowledge of the key active normal modes that promote selectively the population of specific electronic excited states opens a route toward optical control by selectively exciting these modes in order to drive the associated nonadiabatic processes. Relevant simulations, over 2 ps, are proposed to assess the impact of these selective vibrational excitations on the branching ratio between the primary photoproducts, namely, bridge-acceptor charge-transfer (CT) and donor-acceptor charge-separated (CS) electronic states. Whereas the excitation of the localized acetylide bridge C≡C bond stretching does not modify drastically the population of the low-lying electronic states within the first two ps, vibrational excitation of the out-of-plane twisting motion of the N-benzyl group linked to the donor entity favors the population of the 1,3CS states at the expense of the lowest 1,3CT states. This quantum study opens the route to IR optical control experiments based on the specific alteration of vibrational normal modes that activate vibronic couplings between key electronic excited states. However, the presence of critical crossings along the PES channels associated with these normal modes and the role of concurrent SOC driven ultrafast transfers of population should not be underestimated.

Predicting the photodynamics of cyclobutanone triggered by a laser pulse at 200 nm and its MeV-UED signals-A trajectory surface hopping and XMS-CASPT2 perspective

This work is part of a prediction challenge that invited theoretical/computational chemists to predict the photochemistry of cyclobutanone in the gas phase, excited at 200 nm by a laser pulse, and the expected signal that will be recorded during a time-resolved megaelectronvolt ultrafast electron diffraction (MeV-UED). We present here our theoretical predictions based on a combination of trajectory surface hopping with XMS-CASPT2 (for the nonadiabatic molecular dynamics) and Born-Oppenheimer molecular dynamics with MP2 (for the athermal ground-state dynamics following internal conversion), coined (NA+BO)MD. The initial conditions were sampled from Born-Oppenheimer molecular dynamics coupled to a quantum thermostat. Our simulations indicate that the main photoproducts after 2 ps of dynamics are CO + cyclopropane (50%), CO + propene (10%), and ethene and ketene (34%). The photoexcited cyclobutanone in its second excited electronic state S2 can follow two pathways for its nonradiative decay: (i) a ring-opening in S2 and a subsequent rapid decay to the ground electronic state, where the photoproducts are formed, or (ii) a transfer through a closed-ring conical intersection to S1, where cyclobutanone ring opens and then funnels to the ground state. Lifetimes for the photoproduct and electronic populations were determined. We calculated a stationary MeV-UED signal [difference pair distribution function-ΔPDF(r)] for each (interpolated) pathway as well as a time-resolved signal [ΔPDF(r,t) and ΔI/I(s,t)] for the full swarm of (NA+BO)MD trajectories. Furthermore, our analysis provides time-independent basis functions that can be used to fit the time-dependent experimental UED signals [both ΔPDF(r,t) and ΔI/I(s,t)] and potentially recover the population of photoproducts. We also offer a detailed analysis of the limitations of our model and their potential impact on the predicted experimental signals.

Analogies between photochemical reactions and ground-state post-transition-state bifurcations shed light on dynamical origins of selectivity

Revealing the origins of kinetic selectivity is one of the premier tasks of applied theoretical organic chemistry, and for many reactions, doing so involves comparing competing transition states. For some reactions, however, a single transition state leads directly to multiple products, in which case non-statistical dynamic effects influence selectivity control. The selectivity of photochemical reactions-where crossing between excited-state and ground-state surfaces occurs near ground-state transition structures that interconvert competing products-also should be controlled by the momentum of the reacting molecules as they return to the ground state in addition to the shape of the potential energy surfaces involved. Now, using machine-learning-assisted non-adiabatic molecular dynamics and multiconfiguration pair-density functional theory, these factors are examined for a classic photochemical reaction-the deazetization of 2,3-diazabicyclo[2.2.2]oct-2-ene-for which we demonstrate that momentum dominates the selectivity for hexadiene versus [2.2.2] bicyclohexane products.

Water-Mediated Charge Transfer and Electron Localization in a Co3Fe2 Cyanide-Bridged Trigonal Bipyramidal Complex

The effects of temperature and chemical environment on a pentanuclear cyanide-bridged, trigonal bipyramidal molecular paramagnet have been investigated. Using element- and oxidation state-specific near-ambient pressure X-ray photoemission spectroscopy (NAP-XPS) to probe charge transfer and second order, nonlinear vibrational spectroscopy, which is sensitive to symmetry changes based on charge (de)localization coupled with DFT, a detailed picture of environmental effects on charge-transfer-induced spin transitions is presented. The molecular cluster, Co3Fe2(tmphen)6(μ-CN)6(t-CN)6, abbrev. Co3Fe2, shows changes in electronic behavior depending on the chemical environment. NAP-XPS shows that temperature changes induce a metal-to-metal charge transfer (MMCT) in Co3Fe2 between a Co and Fe center, while cycling between ultrahigh vacuum and 2 mbar of water at constant temperature causes oxidation state changes not fully captured by the MMCT picture. Sum frequency generation vibrational spectroscopy (SFG-VS) probes the role of the cyanide ligand, which controls the electron (de)localization via the superexchange coupling. Spectral shifts and intensity changes indicate a change from a charge delocalized, Robin-Day class II/III high spin state to a charge-localized, class I low spin state consistent with DFT. In the presence of a H-bonding solvent, the complex adopts a localized electronic structure, while removal of the solvent delocalizes the charges and drives an MMCT. This change in Robin-Day classification of the complex as a function of chemical environment results in reversible switching of the dipole moment, analogous to molecular multiferroics. These results illustrate the important role of the chemical environment and solvation on underlying charge and spin transitions in this and related complexes.

On-the-fly simulation of time-resolved fluorescence spectra and anisotropy

We combine on-the-fly trajectory surface hopping simulations and the doorway-window representation of nonlinear optical response functions to create an efficient protocol for the evaluation of time- and frequency-resolved fluorescence (TFRF) spectra and anisotropies of the realistic polyatomic systems. This approach gives the effective description of the proper (e.g., experimental) pulse envelopes, laser field polarizations, and the proper orientational averaging of TFRF signals directly from the well-established on-the-fly nonadiabatic dynamic simulations without extra computational cost. To discuss the implementation details of the developed protocol, we chose cis-azobenzene as a prototype to simulate the time evolution of the TFRF spectra governed by its nonadiabatic dynamics. The results show that the TFRF is determined by the interplay of several key factors, i.e., decays of excited-state populations, evolution of the transition dipole moments along with the dynamic propagation, and scaling factor of the TFRF signals associated with the cube of emission frequency. This work not only provides an efficient and effective approach to simulate the TFRF and anisotropies of realistic polyatomic systems but also discusses the important relationship between the TFRF signals and the underlining nonadiabatic dynamics.

Artificial-Intelligence-Enhanced On-the-Fly Simulation of Nonlinear Time-Resolved Spectra

Time-resolved spectroscopy is an important tool for unraveling the minute details of structural changes in molecules of biological and technological significance. The nonlinear femtosecond signals detected for such systems must be interpreted, but it is a challenging task for which theoretical simulations are often indispensable. Accurate simulations of transient absorption or two-dimensional electronic spectra are, however, computationally very expensive, prohibiting the wider adoption of existing first-principles methods. Here, we report an artificial-intelligence-enhanced protocol to drastically reduce the computational cost of simulating nonlinear time-resolved electronic spectra, which makes such simulations affordable for polyatomic molecules of increasing size. The protocol is based on the doorway-window approach for the on-the-fly surface-hopping simulations. We show its applicability for the prototypical molecule of pyrazine for which it produces spectra with high precision with respect to ab initio reference while cutting the computational cost by at least 95% compared to pure first-principles simulations.

Accidental triplet harvesting in donor-acceptor dyads with low spin-orbit coupling

We present an accidental mechanism for efficient intersystem crossing (ISC) between singlet and triplet states with low spin-orbit coupling (SOC) in molecules having donor-acceptor (D-A) moieties separated by a Sigma bond. Our study shows that SOC between the lowest singlet excited state and the higher-lying triplet states, together with nuclear motion-driven coupling of this triplet state with lower-lying triplet states during the free rotation about a Sigma bond, is one of the possible ways to achieve the experimentally observed ISC rate for a class of D-A type photoredox catalysts. This mechanism is found to be the dominant contributor to the ISC process with the corresponding rate reaching a maximum at a dihedral angle in the range of 72°-78° between the D-A moieties of 10-(naphthalen-1-yl)-3,7-diphenyl-10H-phenoxazine and other molecules included in the study. We have further demonstrated that the same mechanism is operative in a specific spirobis[anthracene]dione molecule, where the D and A moieties are interlocked near to the optimal dihedral angle, indicating the plausible effectiveness of the proposed mechanism. The present finding is expected to have implications in strategies for the synthesis of new generations of triplet-harvesting organic molecules.

Assessment of the Electron Correlation Treatment on the Quantum-Classical Dynamics of Retinal Protonated Schiff Base Models: XMS-CASPT2, RMS-CASPT2, and REKS Methods

We compare the performance of three different multiconfigurational wave function-based electronic structure methods and two implementations of the spin-restricted ensemble-referenced Kohn-Sham (REKS) method. The study is characterized by three features: (i) it uses a small set of quantum-classical trajectories rather than potential energy surface mapping, (ii) it focuses, exclusively, on the photoisomerization of retinal protonated Schiff base models, and (iii) it probes the effect of both methyl substitution and the increase in length of the conjugate π-system. For each tested method, the corresponding analytical gradients are used to drive the quantum-classical (Tully's FSSH method) trajectory propagation, including the recent multistate XMS-CASPT2 and RMS-CASPT2 gradients. It is shown that while CASSCF, XMS-CASPT2, and RMS-CASPT2 yield consistent photoisomerization dynamics descriptions, REKS produces, in some of these systems, qualitatively different behavior that is attributed to a flatter and topographically different excited state potential energy surface. The origin of this behavior can be traced back to the effect of the employed density functional approximation. The above studies are further expanded by benchmarking, at the CASSCF and REKS levels, the electronic structure methods using a QM/MM model of the visual pigment rhodopsin.

What is Missing in the Mean Field Description of Spatial Distribution of Population? Important Role of Auxiliary Wave Packets in Trajectory Branching

When the traditional Ehrenfest mean field approach is employed to simulate nonadiabatic dynamics, an effective wave packet (WP) on the average potential energy surface (PES) is utilized to describe the nuclear motion. In the fully quantum picture, however, the WP components on different adiabatic PESs gradually separate in space because they evolve under different velocities and forces. Due to trajectory branching of the WP components, proper decoherence needs to be taken into account, and the spatial distribution of population cannot be described by a single effective WP. Here, we propose an auxiliary branching corrected mean field (A-BCMF) method, where trajectories of auxiliary WPs on adiabatic PESs are introduced. As benchmarked in the three standard Tully models, A-BCMF not only gives correct channel populations but also captures an accurate time-dependent spatial distribution of population. Thereby, we reveal the important role of auxiliary WPs in solving intrinsic problems of the widely used mean field description of nonadiabatic dynamics.

Galván I, Alavi A, Aleotti F, Aquilante F, Autschbach J, Avagliano D, Baiardi A, Bao JJ, Battaglia S, Birnoschi L, Blanco-González A, Bokarev SI, Broer R, Cacciari R, Calio PB, Carlson RK, Carvalho Couto R, Cerdán L, Chibotaru LF, Chilton NF, Church JR, Conti I, Coriani S, Cuéllar-Zuquin J, Daoud RE, Dattani N, Decleva P, de Graaf C, Delcey M, De Vico L, Dobrautz W, Dong SS, Feng R, Ferré N, Filatov(Gulak) M, Gagliardi L, Garavelli M, González L, Guan Y, Guo M, Hennefarth MR, Hermes MR, Hoyer CE, Huix-Rotllant M, Jaiswal VK, Kaiser A, Kaliakin DS, Khamesian M, King DS, Kochetov V, Krośnicki M, Kumaar AA, Larsson ED, Lehtola S, Lepetit MB, Lischka H, López Ríos P, Lundberg M, Ma D, Mai S, Marquetand P, Merritt ICD, Montorsi F, Mörchen M, Nenov A, Nguyen VHA, Nishimoto Y, Oakley MS, Olivucci M, Oppel M, Padula D, Pandharkar R, Phung QM, Plasser F, Raggi G, Rebolini E, Reiher M, Rivalta I, Roca-Sanjuán D, Romig T, Safari AA, Sánchez-Mansilla A, Sand AM, Schapiro I, Scott TR, Segarra-Martí J, Segatta F, Sergentu DC, Sharma P, Shepard R, Shu Y, Staab JK, Straatsma TP, Sørensen LK, Tenorio BNC, Truhlar DG, Ungur L, Vacher M, Veryazov V, Voß TA, Weser O, Wu D, Yang X, Yarkony D, Zhou C, Zobel JP, Lindh R. The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.

A Photoreactor-Interfaced Mass Spectrometer: An Online Platform to Monitor Photochemical Reactions

An experimental platform is reported that allows for the online characterization of photochemical reactions by coupling a continuous flow photoreactor, equipped with LED light irradiation and a dual-tipped ESI source, directly to a mass spectrometer with electrospray ionization. The capabilities of this platform are demonstrated with two classes of photoreactions: (1) the photopolymerization of methyl methacrylate and (2) photocatalyzed alkyne insertion into a 1,2,3-benzotriazinone. The online technique provides rapid information to inform the underlying photochemical mechanism and evaluate the overall photochemistry.

Zeno and Anti-Zeno Effects in Nonadiabatic Molecular Dynamics

Decoherence plays an important role in nonadiabatic (NA) molecular dynamics (MD) simulations because it provides a physical mechanism for trajectory hopping and can alter transition rates by orders of magnitude. Generally, decoherence effects slow quantum transitions, as exemplified by the quantum Zeno effect: in the limit of infinitely fast decoherence, the transitions stop. If the measurements are not sufficiently frequent, an opposite quantum anti-Zeno effect occurs, in which the transitions are accelerated with faster decoherence. Using two common NA-MD approaches, fewest switches surface hopping and decoherence-induced surface hopping, combined with analytic examination, we demonstrate that including decoherence into NA-MD slows down NA transitions; however, many realistic systems operate in the anti-Zeno regime. Therefore, it is important that NA-MD methods describe both Zeno and anti-Zeno effects. Numerical simulations of charge trapping and relaxation in graphitic carbon nitride suggest that time-dependent NA Hamiltonians encountered in realistic systems produce robust results with respect to errors in the decoherence time, a favorable feature for NA-MD simulations.

Photoinduced Aryl Transfer from Imidazolyl-Quinoline π-Conjugated Systems

Aryl transfer between heteroatoms was photochemically available through radical initiation followed by a bimolecular reaction. However, such an excited-state reaction has rarely been reported through a photoinduced intramolecular pathway in the π-conjugated systems. Herein, we found, for the first time, a clean photoinduced intramolecular aryl shift for imidazolyl-quinoline derivatives 2NQ (imidazophenanthrene) and 4NQX (imidazophenanthroline), of which the photoproducts are thermally reversible. Upon light irradiation of the studied compounds in solution, an appreciable blue fluorescence along with a gradual change in color appearance was observed, the photoluminescence and photoconversion quantum yields of which were shown to be competitive in the same excited state. We were able to harness the photoconversion quantum yields of the NQ compounds with facile electronic modifications. These, in combination with time-resolved studies on the NQ compounds, gave an oxygen-insensitive aryl transfer rate within 1-100 ns. The anomalously slow intramolecular reaction rates were further proven to be associated with the ∼5.0 kcal/mol transition free energy. The photoproducts NQ_rs were isolated, identified by X-ray analyses, and also shown to demonstrate anti-Vavilov reverse reactions back to the NQ compounds in the higher-lying excited state. The discovery of photoinduced intramolecular aryl transfer paves a new pathway in the synthetic field, which may also be extended and far-reaching to solar-chemical storage under an appropriate design strategy.

Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Bidirectional Long Short-Term Memory Networks

Essential for understanding far-from-equilibrium processes, nonadiabatic (NA) molecular dynamics (MD) requires expensive calculations of the excitation energies and NA couplings. Machine learning (ML) can simplify computation; however, the NA Hamiltonian requires complex ML models due to its intricate relationship to atomic geometry. Working directly in the time domain, we employ bidirectional long short-term memory networks (Bi-LSTM) to interpolate the Hamiltonian. Applying this multiscale approach to three metal-halide perovskite systems, we achieve two orders of magnitude computational savings compared to direct ab initio calculation. Reasonable charge trapping and recombination times are obtained with NA Hamiltonian sampling every half a picosecond. The Bi-LSTM-NAMD method outperforms earlier models and captures both slow and fast time scales. In combination with ML force fields, the methodology extends NAMD simulation times from picoseconds to nanoseconds, comparable to charge carrier lifetimes in many materials. Nanosecond sampling is particularly important in systems containing defects, boundaries, interfaces, etc. that can undergo slow rearrangements.

Recent Progress on Fluorescent Probes in Heavy Metal Determinations for Food Safety: A Review

One of the main challenges faced in food safety is the accumulation of toxic heavy metals from environmental sources, which can sequentially endanger human health when they are consumed. It is invaluable to establish a practical assay for the determination of heavy metals for food safety. Among the current detection methods, technology based on fluorescent probes, with the advantages of sensitivity, convenience, accuracy, cost, and reliability, has recently shown pluralistic applications in the food industry, which is significant to ensure food safety. Hence, this review systematically presents the recent progress on novel fluorescent probes in determining heavy metals for food safety over the past five years, according to fluorophores and newly emerging sensing cores, which could contribute to broadening the prospects of fluorescent materials and establishing more practical assays for heavy metal determinations.

Spin-Forbidden Addition of Molecular Oxygen to Stable Enol Intermediates-Decarboxylation of 2-Methyl-1-tetralone-2-carboxylic Acid

The deprotonation of an organic substrate is a common preactivation step for the enzymatic cofactorless addition of O2 to this substrate, as it promotes charge-transfer between the two partners, inducing intersystem crossing between the triplet and singlet states involved in the process. Nevertheless, the spin-forbidden addition of O2 to uncharged ligands has also been observed in the laboratory, and the detailed mechanism of how the system circumvents the spin-forbiddenness of the reaction is still unknown. One of these examples is the cofactorless peroxidation of 2-methyl-3,4-dihydro-1-naphthol, which will be studied computationally using single and multi-reference electronic structure calculations. Our results show that the preferred mechanism is that in which O2 picks a proton from the substrate in the triplet state, and subsequently hops to the singlet state in which the product is stable. For this reaction, the formation of the radical pair is associated with a higher barrier than that associated with the intersystem crossing, even though the absence of the negative charge leads to relatively small values of the spin-orbit coupling.

Minimal Auxiliary Basis Set Approach for the Electronic Excitation Spectra of Organic Molecules

We report a minimal auxiliary basis model for time-dependent density functional theory (TDDFT) with hybrid density functionals that can accurately reproduce excitation energies and absorption spectra from TDDFT while reducing cost by about 2 orders of magnitude. Our method, dubbed TDDFT-ris, employs the resolution-of-the-identity technique with just one s-type auxiliary basis function per atom for the linear response operator, where the Gaussian exponents are parametrized across the periodic table using tabulated atomic radii with a single global scaling factor. By tuning on a small test set, we determine a single functional-independent scale factor that balances errors in excitation energies and absorption spectra. Benchmarked on organic molecules and compared to standard TDDFT, TDDFT-ris has an average energy error of only 0.06 eV and yields absorption spectra in close agreement with TDDFT. Thus, TDDFT-ris enables simulation of realistic absorption spectra in large molecules that would be inaccessible from standard TDDFT.

Nonadiabatic Dynamics in a Continuous Circularly Polarized Laser Field with Floquet Phase-Space Surface Hopping

Nonadiabatic chemical reactions involving continuous circularly polarized light (cw CPL) have not attracted as much attention as dynamics in unpolarized/linearly polarized light. However, including circularly (in contrast to linearly) polarized light allows one to effectively introduce a complex-valued time-dependent Hamiltonian, which offers a new path for control or exploration through the introduction of Berry forces. Here, we investigate several inexpensive semiclassical approaches for modeling such nonadiabatic dynamics in the presence of a time-dependent complex-valued Hamiltonian, beginning with a straightforward instantaneous adiabatic fewest-switches surface hopping (IA-FSSH) approach (where the electronic states depend on position and time), continuing to a standard Floquet fewest switches surface hopping (F-FSSH) approach (where the electronic states depend on position and frequency), and ending with an exotic Floquet phase-space surface hopping (F-PSSH) approach (where the electronic states depend on position, frequency, and momentum). Using a set of model systems with time-dependent complex-valued Hamiltonians, we show that the Floquet phase-space adiabats are the optimal choice of basis as far as accounting for Berry phase effects and delivering accuracy. Thus, the F-PSSH algorithm sets the stage for future modeling of nonadiabatic dynamics under strong externally pumped circular polarization.

Generalized Energy-Based Fragmentation Approach for the Electronic Emission Spectra of Large Systems

The excited-state (ES) geometry optimization and electronic emission (fluorescence and phosphorescence) spectra and the ES vibrational spectra of large systems are great challenges in quantum chemistry. In this work, we develop a generalized energy-based fragmentation (GEBF) approach to compute the localized ES structures and vibrational frequencies of large systems. In this approach, the ES energy derivatives (gradients or Hessians) for a localized ES of a large system can be obtained by combining the ES energy derivatives of the corresponding active subsystems (including local excitation center) and the ground-state energy derivatives of inactive subsystems. Two strategies are adopted to overcome two difficulties from state-classification and state-tracking for treating specific ESs. First, for state-classification, we develop an improved density-based spatial clustering applied with noise algorithm with a modified transition orbital projection (TOP) algorithm, which allow a certain ES energy and energy derivatives of the whole system to be calculated with different ES energies and energy derivatives of active subsystems. Furthermore, we also employ the TOP algorithm for tracking the ESs in their geometry optimizations at the time-dependent density functional theory (TDDFT) level. Then, the GEBF approach is applied to investigate the optimized ES geometries or ES vibrational frequencies for two typical systems. Our results show that the cost-effective GEBF approach can accurately reproduce the TDDFT fluorescence spectra of the cytosine derivative and the experimental phosphorescence spectra of the β-cyclodextrin derivative. The GEBF approach is expected to be routinely applied to investigate the electronic emission spectra of very large systems with local chromophores.

Fewest-Switches Surface Hopping with Long Short-Term Memory Networks

The mixed quantum-classical dynamical simulation is essential for studying nonadiabatic phenomena in photophysics and photochemistry. In recent years, many machine learning models have been developed to accelerate the time evolution of the nuclear subsystem. Herein, we implement long short-term memory (LSTM) networks as a propagator to accelerate the time evolution of the electronic subsystem during the fewest-switches surface hopping (FSSH) simulations. A small number of reference trajectories are generated using the original FSSH method, and then the LSTM networks can be built, accompanied by careful examination of typical LSTM-FSSH trajectories that employ the same initial condition and random numbers as the corresponding reference. The constructed network is applied to FSSH to further produce a trajectory ensemble to reveal the mechanism of nonadiabatic processes. Taking Tully's three models as test systems, we qualitatively reproduced the collective results. This work demonstrates that LSTM can be applied to the most popular surface hopping simulations.

Nonadiabatic excited-state dynamics of ReCl(CO)3(bpy) in two different solvents

We present a study of excited-states relaxation of the complex ReCl(CO)₃(bpy) (bpy = 2,2-bipyridine) using a nonadiabatic TD-DFT dynamics on spin-mixed potential energy surfaces in explicit acetonitrile (ACN) and dimethylsulfoxide (DMSO) solutions up to 800 fs. ReCl(CO)₃(bpy) belongs to a group of important photosensitizers which show ultrafast biexponential subpicosecond fluorescence decay kinetics. The choice of solvents was motivated by the different excited-state relaxation dynamics observed in subpicosecond time-resolved IR (TRIR) experiments. Simulations of intersystem crossing (ISC) showed the development of spin-mixed states in both solvents. Transformation of time-dependent populations of spin-mixed states enabled to monitor the temporal evolution of individual singlet and triplet states, fitting of bi-exponential decay kinetics, and simulating the time-resolved fluorescence spectra that show only minor differences between the two solvents. Analysis of structural relaxation and solvent reorganization employing time-resolved proximal distribution functions pointed to the factors influencing the fluorescence decay time constants. Nonadiabatic dynamics simulations of time-evolution of electronic, molecular, and solvent structures emerge as a powerful technique to interpret time-resolved spectroscopic data and ultrafast photochemical reactivity.

A Review on Mechanochemistry: Approaching Advanced Energy Materials with Greener Force

Mechanochemistry with solvent-free and environmentally friendly characteristics is one of the most promising alternatives to traditional liquid-phase-based reactions, demonstrating epoch-making significance in the realization of different types of chemistry. Mechanochemistry utilizes mechanical energy to promote physical and chemical transformations to design complex molecules and nanostructured materials, encourage dispersion and recombination of multiphase components, and accelerate reaction rates and efficiencies via highly reactive surfaces. In particular, mechanochemistry deserves special attention because it is capable of endowing energy materials with unique characteristics and properties. Herein, the latest advances and progress in mechanochemistry for the preparation and modification of energy materials are reviewed. An outline of the basic knowledge, methods, and characteristics of different mechanochemical strategies is presented, distinguishing this review from most mechanochemistry reviews that only focus on ball-milling. Next, this outline is followed by a detailed and insightful discussion of mechanochemistry-involved energy conversion and storage applications. The discussion comprehensively covers aspects of energy transformations from mechanical/optical/chemical energy to electrical energy. Finally, next-generation advanced energy materials are proposed. This review is intended to bring mechanochemistry to the frontline and guide this burgeoning field of interdisciplinary research for developing advanced energy materials with greener mechanical force.

Structural Disorder in Higher-Temperature Phases Increases Charge Carrier Lifetimes in Metal Halide Perovskites

Solar cells and optoelectronic devices are exposed to heat that degrades performance. Therefore, elucidating temperature-dependent charge carrier dynamics is essential for device optimization. Charge carrier lifetimes decrease with temperature in conventional semiconductors. The opposite, anomalous trend is observed in some experiments performed with MAPbI₃ (MA = CH₃NH₃⁺) and other metal halide perovskites. Using ab initio quantum dynamics simulation, we establish the atomic mechanisms responsible for nonradiative electron-hole recombination in orthorhombic-, tetragonal-, and cubic MAPbI₃. We demonstrate that structural disorder arising from the phase transitions is as important as the disorder due to heating in the same phase. The carrier lifetimes grow both with increasing temperature in the same phase and upon transition to the higher-temperature phases. The increased lifetime is rationalized by structural disorder that induces partial charge localization, decreases nonadiabatic coupling, and shortens quantum coherence. Inelastic and elastic electron-vibrational interactions exhibit opposite dependence on temperature and phase. The partial disorder and localization arise from thermal motions of both the inorganic lattice and the organic cations and depend significantly on the phase. The structural deformations induced by thermal fluctuations and phase transitions are on the same order as deformations induced by defects, and hence, thermal disorder plays a very important role. Since charge localization increases carrier lifetimes but inhibits transport, an optimal regime maximizing carrier diffusion can be designed, depending on phase, temperature, material morphology, and device architecture. The atomistic mechanisms responsible for the enhanced carrier lifetimes at elevated temperatures provide guidelines for the design of improved solar energy and optoelectronic materials.

Large-Scale Benchmarking of Multireference Vertical-Excitation Calculations via Automated Active-Space Selection

We have calculated state-averaged complete-active-space self-consistent-field (SA-CASSCF), multiconfiguration pair-density functional theory (MC-PDFT), hybrid MC-PDFT (HMC-PDFT), and n-electron valence state second-order perturbation theory (NEVPT2) excitation energies with the approximate pair coefficient (APC) automated active-space selection scheme for the QUESTDB benchmark database of 542 vertical excitation energies. We eliminated poor active spaces (20–40% of calculations) by applying a threshold to the SA-CASSCF absolute error. With the remaining calculations, we find that NEVPT2 performance is significantly impacted by the size of the basis set the wave functions are converged in, regardless of the quality of their description, which is a problem absent in MC-PDFT. Additionally, we find that HMC-PDFT is a significant improvement over MC-PDFT with the translated PBE (tPBE) density functional and that it performs about as well as NEVPT2 and second-order coupled cluster on a set of 373 excitations in the QUESTDB database. We optimized the percentage of SA-CASSCF energy to include in HMC-PDFT when using the tPBE on-top functional, and we find the 25% value used in tPBE0 to be optimal. This work is by far the largest benchmarking of MC-PDFT and HMC-PDFT to date, and the data produced in this work are useful as a validation of HMC-PDFT and of the APC active-space selection scheme. We have made all the wave functions produced in this work (orbitals and CI vectors) available to the public and encourage the community to utilize this data as a tool in the development of further multireference model chemistries.

Deep learning study of tyrosine reveals that roaming can lead to photodamage

Amino acids are among the building blocks of life, forming peptides and proteins, and have been carefully 'selected' to prevent harmful reactions caused by light. To prevent photodamage, molecules relax from electronic excited states to the ground state faster than the harmful reactions can occur; however, such photochemistry is not fully understood, in part because theoretical simulations of such systems are extremely expensive-with only smaller chromophores accessible. Here, we study the excited-state dynamics of tyrosine using a method based on deep neural networks that leverages the physics underlying quantum chemical data and combines different levels of theory. We reveal unconventional and dynamically controlled 'roaming' dynamics in excited tyrosine that are beyond chemical intuition and compete with other ultrafast deactivation mechanisms. Our findings suggest that the roaming atoms are radicals that can lead to photodamage, offering a new perspective on the photostability and photodamage of biological systems.

Ultrafast Intersystem Crossing Dynamics of 6-Selenoguanine in Water

Rationalizing the photochemistry of nucleobases where an oxygen is replaced by a heavier atom is essential for applications that exploit near-unity triplet quantum yields. Herein, we report on the ultrafast excited-state deactivation mechanism of 6-selenoguanine (6SeGua) in water by combining nonadiabatic trajectory surface-hopping dynamics with an electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) scheme. We find that the predominant relaxation mechanism after irradiation starts on the bright singlet S₂ state that converts internally to the dark S₁ state, from which the population is transferred to the triplet T₂ state via intersystem crossing and finally to the lowest T₁ state. This S₂ → S₁ → T₂ → T₁ deactivation pathway is similar to that observed for the lighter 6-thioguanine (6tGua) analogue, but counterintuitively, the T₁ lifetime of the heavier 6SeGua is shorter than that of 6tGua. This fact is explained by the smaller activation barrier to reach the T₁/S₀ crossing point and the larger spin-orbit couplings of 6SeGua compared to 6tGua. From the dynamical simulations, we also calculate transient absorption spectra (TAS), which provide two time constants (τ₁ = 131 fs and τ₂ = 191 fs) that are in excellent agreement with the experimentally reported value (τ_exp = 130 ± 50 fs) (Farrel et al. J. Am. Chem. Soc. 2018, 140, 11214). Intersystem crossing itself is calculated to occur with a time scale of 452 ± 38 fs, highlighting that the TAS is the result of a complex average of signals coming from different nonradiative processes and not intersystem crossing alone.

A phase-space semiclassical approach for modeling nonadiabatic nuclear dynamics with electronic spin

Chemical relaxation phenomena, including photochemistry and electron transfer processes, form a vigorous area of research in which nonadiabatic dynamics plays a fundamental role. However, for electronic systems with spin degrees of freedom, there are few if any applicable and practical quasiclassical methods. Here, we show that for nonadiabatic dynamics with two electronic states and a complex-valued Hamiltonian that does not obey time-reversal symmetry (as relevant to many coupled nuclear-electronic-spin systems), the optimal semiclassical approach is to generalize Tully’s surface hopping dynamics from coordinate space to phase space. In order to generate the relevant phase-space adiabatic surfaces, one isolates a proper set of diabats, applies a phase gauge transformation, and then diagonalizes the total Hamiltonian (which is now parameterized by both R and P). The resulting algorithm is simple and valid in both the adiabatic and nonadiabatic limits, incorporating all Berry curvature effects. Most importantly, the resulting algorithm allows for the study of semiclassical nonadiabatic dynamics in the presence of spin–orbit coupling and/or external magnetic fields. One expects many simulations to follow as far as modeling cutting-edge experiments with entangled nuclear, electronic, and spin degrees of freedom, e.g., experiments displaying chiral-induced spin selectivity.

Hydrolysis and photolysis of flupyradifurone in aqueous solution and natural water: Degradation kinetics and pathway

Flupyradifurone (FPO) easily spreads to the water environment after application because of its high solubility in water (3200 mg/L, 20 °C), but as a novel neonicotinoid pesticide, its environmental fate study is still lacking. Here, laboratory experiments were conducted to investigate the degradation kinetics and pathways of FPO in aqueous solutions and natural waters. The results showed that FPO was fairly stable in water under natural conditions (the hydrolysis half-lives at 15 °C, 25 °C, and 35 °C were >150 d, and the photolysis half-lives under sunlight were >168 h). However, FPO was photodegraded rapidly under ultraviolet (UV) light (half-lives of 2.37-3.81 min). Then, indirect photolysis under UV light was examined with the addition of photosensitizers, revealing that direct photolysis is the main FPO degradation pathway in water, and the contribution of indirect photolysis was limited. Moreover, two photoproducts were separated, purified and collected via preparative HPLC, and identified via high resolution mass spectrometry. Then, the plausible photolysis pathway was proposed. The results of this study will contribute to a better understanding of the fate of FPO in the water environment.

Electron-Volt Fluctuation of Defect Levels in Metal Halide Perovskites on a 100 ps Time Scale

Metal halide perovskites (MHPs) have gained considerable attention due to their excellent optoelectronic performance, which is often attributed to unusual defect properties. We demonstrate that midgap defect levels can exhibit very large and slow energy fluctuations associated with anharmonic acoustic motions. Therefore, care should be taken classifying MHP defects as deep or shallow, since shallow defects may become deep and vice versa. As a consequence, charges from deep levels can escape into bands, and light absorption can be extended to longer wavelengths, improving material performance. The phenomenon, demonstrated with iodine vacancy in CH₃NH₃PbI₃ using a machine learning force field, can be expected for a variety of defects and dopants in many MHPs and other soft inorganic semiconductors. Since large-scale anharmonic motions can be precursors to chemical decomposition, a known problem with MHPs, we propose that materials that are stiffer than MHPs but softer than traditional inorganic semiconductors, such as Si and TiO₂, may simultaneously exhibit excellent performance and stability.

Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential

Light-induced chemical processes are ubiquitous in nature and have widespread technological applications. For example, photoisomerization can allow a drug with a photo-switchable scaffold such as azobenzene to be activated with light. In principle, photoswitches with desired photophysical properties like high isomerization quantum yields can be identified through virtual screening with reactive simulations. In practice, these simulations are rarely used for screening, since they require hundreds of trajectories and expensive quantum chemical methods to account for non-adiabatic excited state effects. Here we introduce a diabatic artificial neural network (DANN), based on diabatic states, to accelerate such simulations for azobenzene derivatives. The network is six orders of magnitude faster than the quantum chemistry method used for training. DANN is transferable to azobenzene molecules outside the training set, predicting quantum yields for unseen species that are correlated with experiment. We use the model to virtually screen 3100 hypothetical molecules, and identify novel species with high predicted quantum yields. The model predictions are confirmed using high-accuracy non-adiabatic dynamics. Our results pave the way for fast and accurate virtual screening of photoactive compounds.

Sampling effects in quantum mechanical/molecular mechanics trajectory surface hopping non-adiabatic dynamics

The impact of different initial conditions in non-adiabatic trajectory surface hopping dynamics within a hybrid quantum mechanical/molecular mechanics scheme is investigated. The influence of a quantum sampling, based on a Wigner distribution, a fully thermal sampling, based on classical molecular dynamics, and a quantum sampled system, but thermally equilibrated with the environment, is investigated on the relaxation dynamics of solvated fulvene after light irradiation. We find that the decay from the first singlet excited state to the ground state shows high dependency on the initial condition and simulation parameters. The three sampling methods lead to different distributions of initial geometries and momenta, which then affect the fate of the excited state dynamics. We evaluated both the effect of sampling geometries and momenta, analysing how the ultrafast decay of fulvene changes accordingly. The results are expected to be of interest to decide how to initialize non-adiabatic dynamics in the presence of the environment. This article is part of the theme issue 'Chemistry without the Born-Oppenheimer approximation'.

Mechanisms, Challenges, and Opportunities of Dual Ni/Photoredox-Catalyzed C(sp2)-C(sp3) Cross-Couplings

The merging of photoredox and nickel catalysis has revolutionized the field of C-C cross-coupling. However, in comparison to the development of synthetic methods, detailed mechanistic investigations of these catalytic systems are lagging. To improve the mechanistic understanding, computational tools have emerged as powerful tools to elucidate the factors controlling reactivity and selectivity in these complex catalytic transformations. Based on the reported computational studies, it appears that the mechanistic picture of catalytic systems is not generally applicable, but is rather dependent on the specific choice of substrate, ligands, photocatalysts, etc. Given the complexity of these systems, the need for more accurate computational methods, readily available and user-friendly dynamics simulation tools, and data-driven approaches is clear in order to understand at the molecular level the mechanisms of these transformations. In particular, we anticipate that such improvement of theoretical methods will become crucial to advance the understanding of excited-state properties and dynamics of key species, as well as to enable faster and unbiased exploration of reaction pathways. Further, with greater collaboration between computational, experimental, and spectroscopic communities, the mechanistic investigation of photoredox/Ni dual-catalytic reactions is expected to thrive quickly, facilitating the design of novel catalytic systems and promoting our understanding of the reaction selectivity.

Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol

In recent years, photoactive proteins such as rhodopsins have become a common target for cutting-edge research in the field of optogenetics. Alongside wet-lab research, computational methods are also developing rapidly to provide the necessary tools to analyze and rationalize experimental results and, most of all, drive the design of novel systems. The Automatic Rhodopsin Modeling (ARM) protocol is focused on providing exactly the necessary computational tools to study rhodopsins, those being either natural or resulting from mutations. The code has evolved along the years to finally provide results that are reproducible by any user, accurate and reliable so as to replicate experimental trends. Furthermore, the code is efficient in terms of necessary computing resources and time, and scalable in terms of both number of concurrent calculations as well as features. In this review, we will show how the code underlying ARM achieved each of these properties.

Low-Scaling Excited State Calculation Using the Block Interaction Product State

We develop an automatic and efficient scheme for the accurate construction of the bases for excitonic models, which can enable "black-box" excited state structure calculations for large molecular systems. These new and optimized bases, which are named the block interaction product state (BIPS), can be expressed as the direct products of the local states for each chromophore. Each chromophore's local states are selected by diagonalization of its reduced density matrix, which is obtained by quantum chemical calculation of the small subsystem composed of the chromophore and its nearest neighbors. We implemented the BIPS framework with fragment-based calculations considering two- and three-body interactions. Test calculations for eight different molecular aggregates demonstrate that this framework provides an accurate description of not only the excitation energies but also the first-order wave function properties (dipole moment and transition dipole moment) of the low-lying excited states at a low-scaling computational cost.

Ultrafast Internal Conversion Dynamics through the on-the-Fly Simulation of Transient Absorption Pump-Probe Spectra with Different Electronic Structure Methods

An on-the-fly surface-hopping simulation protocol is developed for the evaluation of transient absorption (TA) pump-probe (PP) signals of molecular systems exhibiting internal conversion to the electronic ground state. We study the nonadiabatic dynamics of azomethane and the associating TA PP spectra at three levels of the electronic-structure theory, OM2/MRCI, SA-CASSCF, and XMS-CASPT2. The impact of these methods on the population dynamics and time-resolved TA PP signals is substantially different. This difference is attributed to the strong non-Condon effects that must be taken into account for the proper understanding and interpretation of time-resolved TA PP signals of nonadiabatic polyatomic systems. This shows that the combination of the dynamical and spectral simulations definitely provides more accurate and detailed information on the microscopic mechanisms of photophysical and photochemical processes. Hence the simulation of time-resolved spectroscopic signals provides another important dimension to examine the accuracy of quantum chemistry methods.

Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Inverse Fast Fourier Transform

Nonadiabatic (NA) molecular dynamics (MD) allows one to investigate far-from-equilibrium processes in nanoscale and molecular materials at the atomistic level and in the time domain, mimicking time-resolved spectroscopic experiments. Ab initio NAMD is limited to about 100 atoms and a few picoseconds, due to computational cost of excitation energies and NA couplings. We develop a straightforward methodology that can extend ab initio quality NAMD to nanoseconds and thousands of atoms. The ab initio NAMD Hamiltonian is sampled and interpolated along a trajectory using a Fourier transform, and then, it is used to perform NAMD with known algorithms. The methodology relies on the classical path approximation, which holds for many materials and processes. To achieve a complete ab initio quality description, the trajectory can be obtained using an ab initio trained machine learning force field. The method is demonstrated with charge carrier trapping and relaxation in hybrid organic-inorganic and all-inorganic metal halide perovskites that exhibit complex dynamics and are actively studied for optoelectronic applications.

Resolving Chemical Dynamics in Biological Energy Conversion: Long-Range Proton-Coupled Electron Transfer in Respiratory Complex I

Biological energy conversion is catalyzed by membrane-bound proteins that transduce chemical or light energy into energy forms that power endergonic processes in the cell. At a molecular level, these catalytic processes involve elementary electron-, proton-, charge-, and energy-transfer reactions that take place in the intricate molecular machineries of cell respiration and photosynthesis. Recent developments in structural biology, particularly cryo-electron microscopy (cryoEM), have resolved the molecular architecture of several energy transducing proteins, but detailed mechanistic principles of their charge transfer reactions still remain poorly understood and a major challenge for modern biochemical research. To this end, multiscale molecular simulations provide a powerful approach to probe mechanistic principles on a broad range of time scales (femtoseconds to milliseconds) and spatial resolutions (10¹–10⁶ atoms), although technical challenges also require balancing between the computational accuracy, cost, and approximations introduced within the model. Here we discuss how the combination of atomistic (aMD) and hybrid quantum/classical molecular dynamics (QM/MM MD) simulations with free energy (FE) sampling methods can be used to probe mechanistic principles of enzymes responsible for biological energy conversion. We present mechanistic explorations of long-range proton-coupled electron transfer (PCET) dynamics in the highly intricate respiratory chain enzyme Complex I, which functions as a redox-driven proton pump in bacterial and mitochondrial respiratory chains by catalyzing a 300 Å fully reversible PCET process. This process is initiated by a hydride (H^–) transfer between NADH and FMN, followed by long-range (>100 Å) electron transfer along a wire of 8 FeS centers leading to a quinone biding site. The reduction of the quinone to quinol initiates dissociation of the latter to a second membrane-bound binding site, and triggers proton pumping across the membrane domain of complex I, in subunits up to 200 Å away from the active site. Our simulations across different size and time scales suggest that transient charge transfer reactions lead to changes in the internal hydration state of key regions, local electric fields, and the conformation of conserved ion pairs, which in turn modulate the dynamics of functional steps along the reaction cycle. Similar functional principles, which operate on much shorter length scales, are also found in some unrelated proteins, suggesting that enzymes may employ conserved principles in the catalysis of biological energy transduction processes.

Photochemical Hydrogen Evolution at Metal Centers Probed with Hydrated Aluminium Cations, Al+ (H2 O)n , n=1-10

Hydrated aluminium cations have been investigated as a photochemical model system with up to ten water molecules by UV action spectroscopy in a Fourier transform ion cyclotron resonance (FT‐ICR) mass spectrometer. Intense photodissociation was observed starting at 4.5 eV for two to eight water molecules with loss of atomic hydrogen, molecular hydrogen and water molecules. Quantum chemical calculations for n=2 reveal that solvation shifts the intense 3s–3p excitations of Al⁺ into the investigated photon energy range below 5.5 eV. During the photochemical relaxation, internal conversion from S₁ to T₂ takes place, and photochemical hydrogen formation starts on the T₂ surface, which passes through a conical intersection, changing to T₁. On this triplet surface, the electron that was excited to the Al 3p orbital is transferred to a coordinated water molecule, which dissociates into a hydroxide ion and a hydrogen atom. If the system remains in the triplet state, this hydrogen radical is lost directly. If the system returns to singlet multiplicity, the reaction may be reversed, with recombination with the hydroxide moiety and electron transfer back to aluminium, resulting in water evaporation. Alternatively, the hydrogen radical can attack the intact water molecule, forming molecular hydrogen and aluminium dihydroxide. Photodissociation is observed for up to n=8. Clusters with n=9 or 10 occur exclusively as HAlOH⁺(H₂O)_n‐1 and are transparent in the investigated energy range. For n=4–8, a mixture of Al⁺(H₂O)_n and HAlOH⁺(H₂O)_n‐1 is present in the experiment.

Increasing Efficiency of Nonadiabatic Molecular Dynamics by Hamiltonian Interpolation with Kernel Ridge Regression

Nonadiabatic (NA) molecular dynamics (MD) goes beyond the adiabatic Born-Oppenheimer approximation to account for transitions between electronic states. Such processes are common in molecules and materials used in solar energy, optoelectronics, sensing, and many other fields. NA-MD simulations are much more expensive compared to adiabatic MD due to the need to compute excited state properties and NA couplings (NACs). Similarly, application of machine learning (ML) to NA-MD is more challenging compared with adiabatic MD. We develop an NA-MD simulation strategy in which an adiabatic MD trajectory, which can be generated with a ML force field, is used to sample excitation energies and NACs for a small fraction of geometries, while the properties for the remaining geometries are interpolated with kernel ridge regression (KRR). This ML strategy allows for one to perform NA-MD under the classical path approximation, increasing the computational efficiency by over an order of magnitude. Compared to neural networks, KRR requires little parameter tuning, saving efforts on model building. The developed strategy is demonstrated with two metal halide perovskites that exhibit complicated MD and are actively studied for various applications.

A Density Matrix Renormalization Group Study of the Low-Lying Excited States of a Molybdenum Carbonyl-Nitrosyl Complex

A density matrix renormalization group-self consistent field (DMRG-SCF) study has been carried out to calculate the low-lying excited states of CpMo(CO)₂ NO, a molybdenum complex containing NO and CO ligands. In order to automatically select an appropriate active space, a novel procedure employing the maximum single-orbital entropy for several states has been introduced and shown to be efficient and easy-to-implement when several electronic states are simultaneously considered. The analysis of the resulting natural transition orbitals and charge-transfer numbers shows that the lowest five excited electronic states are excitation into metal-NO antibonding orbitals, which offer the possibility for nitric oxide (NO) photorelease after excitation with visible light. Higher excited states are metal-centered excitations with contributions of metal-CO antibonding orbitals, which may serve as a gateway for carbon monoxide (CO) delivery. Time-dependent density functional theory calculations done for comparison, show that the state characters agree remarkably well with those from DMRG-SCF, while excitation energies are 0.4-1.0 eV red-shifted with respect to the DMRG-SCF ones.