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1. The impact of stacking and phonon environment on energy transfer in organic chromophores: computational insights

   https://doi.org/10.1039/D3TC00479A  

   Mukazhanova, Aliya ; Negrin-Yuvero, Hassiel ; Freixas, Victor M. ; Tretiak, Sergei ; Fernandez-Alberti, Sebastian ; Sharifzadeh, Sahar ( April 2023 , Journal of Materials Chemistry C)

   Energy transfer in organic materials is extensively studied due to many applications in optoelectronics. The electronic and vibrational relaxations within molecular assemblies can be influenced by stacking arrangements or additions of a backbone that unites them. Here, we present the computational study of the photoexcitation dynamics of a perylene diimide monomer, and face-to-face stacked dimer and trimer. By using non-adiabatic excited-state molecular dynamics simulations, we show that the non-radiative relaxation is accelerated with the number of stacked molecules. This effect is explained by differences in the energy splitting between states that impacts their corresponding nonadiabatic couplings. Additionally, our analysis of the vibronic dynamics reveals that the passage through the different conical intersections that participate in the relaxation of the stacked systems, activate a positive feedback mechanism. This effect involves a narrow set of vibrational normal modes that accelerate the process by increasing the efficiency of its vibronic dynamics. In contrast, an addition of a biologically inspired backbone slows down the relaxation rate due to its participation in the vibronic dynamics of the molecular stacking arrangements. Our results suggest the stacking arrangements and common backbones as strategies to modulate the efficiency of electronic and vibrational relaxation of diimide-based systems and other molecular aggregates. 

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2. A Theoretical Study of Polarization Selective Two-Dimensional Vibronic Spectroscopies of Multimode Systems

   https://doi.org/10.1364/UP.2020.M4B.20  

   Weakly, Robert B. ; Gaynor, James D. ; Khalil, Munira ( January 2020 , Optica Publishing Group)

   A model vibronic Hamiltonian composed of coupled anharmonic vibrational modes and two electronic states provides a quantitative framework for understanding how vibronic couplings and dipole orientations are encoded in two-dimensional vibronic spectroscopy.

    

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3. Vibronic coherence evolution in multidimensional ultrafast photochemical processes

   https://doi.org/10.1038/s41467-019-13503-9  

   Gaynor, James D. ; Sandwisch, Jason ; Khalil, Munira ( December 2019 , Nature Communications)

   The complex choreography of electronic, vibrational, and vibronic couplings used by photoexcited molecules to transfer energy efficiently is remarkable, but an unambiguous description of the temporally evolving vibronic states governing these processes has proven experimentally elusive. We use multidimensional electronic-vibrational spectroscopy to identify specific time-dependent excited state vibronic couplings involving multiple electronic states, high-frequency vibrations, and low-frequency vibrations which participate in ultrafast intersystem crossing and subsequent relaxation of a photoexcited transition metal complex. We discover an excited state vibronic mechanism driving long-lived charge separation consisting of an initial electronically-localized vibrational wavepacket which triggers delocalization onto two charge transfer states after propagating for ~600 femtoseconds. Electronic delocalization consequently occurs through nonadiabatic internal conversion driven by a 50 cm⁻¹coupling resulting in vibronic coherence transfer lasting for ~1 picosecond. This study showcases the power of multidimensional electronic-vibrational spectroscopy to elucidate complex, non-equilibrium energy and charge transfer mechanisms involving multiple molecular coordinates.

    

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4. Vibronic Relaxation Pathways in Molecular Spin Qubit Na9[Ho(W5O18)2]·35H2O under Pressure

   https://doi.org/10.3390/magnetochemistry9020053  

   Musfeldt, Janice L. ; Liu, Zhenxian ; López-Alcalá, Diego ; Duan, Yan ; Gaita-Ariño, Alejandro ; Baldoví, José J. ; Coronado, Eugenio ( February 2023 , Magnetochemistry)

   In order to explore how spectral sparsity and vibronic decoherence pathways can be controlled in a model qubit system with atomic clock transitions, we combined diamond anvil cell techniques with synchrotron-based far infrared spectroscopy and first-principles calculations to reveal the vibrational response of Na9[Ho(W5O18)2]·35H2O under compression. Because the hole in the phonon density of states acts to reduce the overlap between the phonons and f manifold excitations in this system, we postulated that pressure might move the HoO4 rocking, bending, and asymmetric stretching modes that couple with the MJ = ±5, ±2, and ±7 levels out of resonance, reducing their interactions and minimizing decoherence processes, while a potentially beneficial strategy for some molecular qubits, pressure slightly hardens the phonons in Na9[Ho(W5O18)2]·35H2O and systematically fills in the transparency window in the phonon response. The net result is that the vibrational spectrum becomes less sparse and the overlap with the various MJ levels of the Ho3+ ion actually increases. These findings suggest that negative pressure, achieved using chemical means or elongational strain, could further open the transparency window in this rare earth-containing spin qubit system, thus paving the way for the use of device surfaces and interface elongational/compressive strains to better manage decoherence pathways. 

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5. Machine Learning a Universal Harmonic Interatomic Potential for Predicting Phonons in Crystalline Solids

   Lee, Huiju ; Xia, Yi ( March 2024 , Applied physics letters)

   Grein, Christoph (Ed.)

   Phonons, as quantized vibrational modes in crystalline materials, play a crucial role in determining a wide range of physical properties, such as thermal and electrical conductivity, making their study a cornerstone in materials science. In this study, we present a simple yet effective strategy for deep learning harmonic phonons in crystalline solids by leveraging existing phonon databases and state-of-the-art machine learning techniques. The key of our method lies in transforming existing phonon datasets, primarily represented in interatomic force constants, into a force-displacement representation suitable for training machine learning universal interatomic potentials. By applying our approach to one of the largest phonon databases publicly available, we demonstrate that the resultant machine learning universal harmonic interatomic potential not only accurately predicts full harmonic phonon spectra but also calculates key thermodynamic properties with remarkable precision. Furthermore, the restriction to a harmonic potential energy surface in our model provides a way of assessing uncertainty in machine learning predictions of vibrational properties, essential for guiding further improvements and applications in materials science. 

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