Noticeable differences between the vibrational (IR and Raman) spectra of neat H(2)O and D(2)O ice Ih are observed experimentally. Here, we employ our theoretical mixed quantum/classical approach to investigate these differences. We find reasonable agreement between calculated and experimental line shapes at both high and low temperatures. From understanding the structure of ice Ih and its vibrational exciton Hamiltonian, we provide assignments of the IR and Raman spectral features for both H(2)O and D(2)O ice Ih. We find that in H(2)O ice these features are due to strong and weak intermolecular coupling, not to intramolecular coupling. The differences between H(2)O and D(2)O ice spectra are attributed to the significantly stronger intramolecular coupling in D(2)O ice. Our conclusion for both H(2)O and D(2)O ice is that the molecular symmetric and antisymmetric normal modes do not form a useful basis for understanding OH or OD stretch spectroscopy.

Infrared spectroscopy of the water OH stretch provides a sensitive probe of the local hydrogen-bonding structure and dynamics of water molecules. Previously, we have utilized a mixed quantum/classical model to calculate vibrational spectroscopic observables for bulk water, ice, the liquid/vapor interface, and small water clusters, as well as water interacting with ions and biological molecules. These studies rely on spectroscopic maps that relate the OH stretching frequency and transition dipole to the local environment around a water molecule. Our spectroscopic maps were parametrized based on water clusters taken from bulk water simulations; in this article, we test the robustness of these maps for water in nonbulk-liquid environments. We find that the frequency, transition dipole, and coupling maps work as well for the water surface, ice Ih, and the water hexamer as they do for liquid water. This suggests that these maps may be generally applied to study the vibrational spectroscopy of water in diverse, potentially heterogeneous environments.

We present a unified picture of how OH-stretch spectroscopy in water can be understood in terms of hydrogen bonding for the four systems listed in the title. To understand the strength, and hence OH-stretch frequency, of a hydrogen bond, it is crucial to consider the number of additional acceptor hydrogen bonds made by both the donor and acceptor molecules. This necessity for focusing on the hydrogen-bond environment of both donor and acceptor molecules follows from quantum chemical considerations and is related to the three-body interactions in water. Armed with this understanding we can make a detailed interpretation of the OH-stretch IR absorption spectrum of the cage conformer for HOD(D2O)5 and the imaginary part of the ssp OH-stretch sum-frequency spectrum of the surface of liquid D2O with dilute HOD.

During developmental stages, biomechanical stimuli on cardiac cells modulate genetic programs, and deviations from normal stimuli can lead to cardiac defects. Therefore, it is important to characterize normal cardiac biomechanical stimuli during early developmental stages. Using the chicken embryo model of cardiac development, we focused on characterizing biomechanical stimuli on the Hamburger–Hamilton (HH) 18 chick cardiac outflow tract (OFT), the distal portion of the heart from which a large portion of defects observed in humans originate. To characterize biomechanical stimuli in the OFT, we used a combination of in vivo optical coherence tomography (OCT) imaging, physiological measurements and computational fluid dynamics (CFD) modeling. We found that, at HH18, the proximal portion of the OFT wall undergoes larger circumferential strains than its distal portion, while the distal portion of the OFT wall undergoes larger wall stresses. Maximal wall shear stresses were generally found on the surface of endocardial cushions, which are protrusions of extracellular matrix onto the OFT lumen that later during development give rise to cardiac septa and valves. The non-uniform spatial and temporal distributions of stresses and strains in the OFT walls provide biomechanical cues to cardiac cells that likely aid in the extensive differential growth and remodeling patterns observed during normal development.

Hemodynamic conditions play a critical role in embryonic cardiovascular development, and altered blood flow leads to congenital heart defects. Chicken embryos are frequently used as models of cardiac development, with abnormal blood flow achieved through surgical interventions such as outflow tract (OFT) banding, in which a suture is tightened around the heart OFT to restrict blood flow. Banding in embryos increases blood pressure and alters blood flow dynamics, leading to cardiac malformations similar to those seen in human congenital heart disease. In studying these hemodynamic changes, synchronization of data to the cardiac cycle is challenging, and alterations in the timing of cardiovascular events after interventions are frequently lost. To overcome this difficulty, we used ECG signals from chicken embryos (Hamburger-Hamilton stage 18, ∼3 days of incubation) to synchronize blood pressure measurements and optical coherence tomography images. Our results revealed that, after 2 h of banding, blood pressure and pulse wave propagation strongly depend on band tightness. In particular, while pulse transit time in the heart OFT of control embryos is ∼10% of the cardiac cycle, after banding (35% to 50% band tightness) it becomes negligible, indicating a faster OFT pulse wave velocity. Pulse wave propagation in the circulation is likewise affected; however, pulse transit time between the ventricle and dorsal aorta (at the level of the heart) is unchanged, suggesting an overall preservation of cardiovascular function. Changes in cardiac pressure wave propagation are likely contributing to the extent of cardiac malformations observed in banded hearts.

The dissociation of excited electron–hole pairs is a microscopic process that is fundamental to the performance of photovoltaic systems. For this process to be successful, the oppositely charged electron and hole must overcome an electrostatic binding energy before they undergo ground state recombination. It has been observed previously that the presence of energetic disorder can lead to a reduction in recombination losses. Here we investigate this effect using a simple model of charge dynamics at a donor–acceptor interface. We consider the effect of spatial variations in electronic energy levels, such as those that arise in disordered molecular systems, on dissociation yield and demonstrate that it is maximized with a finite amount of disorder. We demonstrate that this is a nonequilibrium effect that is mediated by the dissipation driven formation of partially dissociated intermediate states that are long-lived because they cannot easily recombine. We present a kinetic model that incorporates these states and show that it is capable of reproducing similar behavior when it is parametrized with nonequilibrium rates.

Accurate spectral densities are necessary for computing realistic exciton dynamics and nonlinear optical spectra of chromophores in condensedphase environments, including multichromophore pigment−protein systems. However, due to the significant computational cost of computing spectral densities from first principles, requiring many thousands of excited-state calculations, most simulations of realistic systems rely on treating the environment as fixed-point charges. Here, using a number of representative systems ranging from solvated chromophores to the photoactive yellow protein (PYP), we demonstrate that the quantum mechanical (QM) electronic polarization of the environment is key to obtaining accurate spectral densities and line shapes within the cumulant framework. We show that the QM environment can enhance or depress the coupling of fast chromophore degrees of freedom to the energy gap, altering the electronic−vibrational coupling and the resulting vibronic progressions in the absorption spectrum. In analyzing the physical origin of peaks in the spectral density, we identify vibrational modes that couple the electron and the hole as being particularly sensitive to the QM screening of the environment. For PYP, we reveal the need for careful determination of the appropriate QM region to obtain reliable spectral densities. Our results indicate that the QM polarization of the environment can be crucial not just for excitation energies but also for electronic−vibrational coupling in complex systems with implications for the correct modeling of linear and nonlinear optical spectroscopy in the condensed phase as well as energy transfer in pigment−protein complexes.

Atomistic modeling of energetic disorder in organic semiconductors (OSCs) and its effects on the optoelectronic properties of OSCs requires a large number of excitedstate electronic-structure calculations, a computationally daunting task for many OSC applications. In this work, we advocate the use of deep learning to address this challenge and demonstrate that state-of-the-art deep neural networks (DNNs) are capable of predicting the electronic properties of OSCs at an accuracy comparable with the quantum chemistry methods used for generating training data. We extensively investigate the performances of four recent DNNs (deep tensor neural network, SchNet, message passing neural network, and multilevel graph convolutional neural network) in predicting various electronic properties of an important class of OSCs, i.e., oligothiophenes (OTs), including their HOMO and LUMO energies, excited-state energies and associated transition dipole moments. We find that SchNet shows the best performance for OTs of different sizes (from bithiophene to sexithiophene), achieving average prediction errors in the range of 20-80meV compared to the results from (time-dependent) density functional theory. We show that SchNet also consistently outperforms shallow feed-forward neural networks, especially in difficult cases with large molecules or limited training data. We further show that SchNet could predict the transition dipole moment accurately, a task previously known to be difficult for feed-forward neural networks, and we ascribe the relatively large errors in transition dipole prediction seen for some OT configurations to the charge-transfer character of their excited states. Finally, we demonstrate the effectiveness of SchNet by modeling the UV-Vis absorption spectra of OTs in dichloromethane and a good agreement is observed between the calculated and experimental spectra. Our results show the great promise of DNNs in depicting the rugged energy landscapes encountered in OSCs, serving as the first step in the atomistic modeling of optoelectronic processes in OSCs relevant to device performances. 2