Stimulated Raman Scattering (SRS) microscopy is a powerful, rapid label-free, and chemical-specific imaging modality. While the underlying physics is well understood and modeled numerically, we show that, with simple approximations, one can derive equations which enable rapid simulations. Here, we develop an analytical model for spectral focusing SRS microscopy, validate it against numerical simulations, and apply it to the analysis of several experimental implementations. Of use to experimentalists, our model permits rapid simulation of advanced modulation schemes for background (non-Raman) signal removal in SRS microscopy. We compare and discuss their relative advantages and drawbacks.

Photogenerated polarons are fundamental to the photophysics of transition metal oxide semiconductors. It is, therefore, imperative to understand the mechanisms by which polarons form upon photoexcitation of transition metal oxides to realize their potential in photoapplications. Hematite (α-Fe2O3) is known to form photoexcited small polarons, which limit its performance as a photoelectrocatalyst for water oxidation. Here, we report a systematic comparison of the electronic, optical, and vibrational properties of hematite to those of other metal oxides in the corundum crystal family that elucidates the impact of d-orbital radius on carrier-phonon coupling. Three corundum metal oxides - α-Al2O3 (no d-electrons), α-Fe2O3 (3d), and α-Rh2O3 (4d) - are analyzed with a combined approach of resonance Raman spectroscopy, thermal difference optical spectroscopy, and computational modeling of electronic and vibrational states. We find that the Raman spectrum of α-Al2O3 does not change as the Raman excitation is varied across the visible region, as there is no optical absorption. In contrast, both α-Fe2O3 and α-Rh2O3 exhibit strong coupling of phonons to optical transitions at the onset of absorption, which is evidence of excitation into a polaronic state. Closely comparing the optical polaronic properties of α-Fe2O3 and α-Rh2O3, we establish that increased lattice covalency in α-Rh2O3 arising from the increased radial extension of the 4d orbitals influences which phonon modes mediate photogenerated polaron formation.

Permittivity values of thin glassy films obtained by physical vapor deposition onto interdigitated electrode cells have been reported to increase considerably after annealing the sample above its glass transition temperature, which cannot be explained by effects of density. While such a change might be interpreted as a transformation to a different structure or altered dynamics, we employ a nonpolar molecular liquid to demonstrate that the apparent permittivity derived from impedance experiments can increase without changes in properties inherent in the sample material. More specifically, it is shown that annealing induces surface flattening that leads to material relocating from on top of the metallic electrode digits to between these digits. For films of thicknesses below 10% of the digit spacing, we demonstrate that the impedance measurement senses predominantly the material located between electrode digits, while being blind to the part of the sample deposited onto the digits. This implies that the apparent permittivity can increase without a change in material properties. A relation that determines film height and deposition rate from the observed capacitance increment is provided.

We report a sensitive new approach for tracking surface hydrogen coverage using the novel high-repetition rate implementation of velocity-resolved kinetics in an investigation of methanol-d4 dehydrogenation on Pt(111) to CO and D2. The reactant beam of methanol-d4 had an incidence kinetic energy of 0.46 eV, and the reaction was studied over a surface temperature range of 700-950 K. The reaction probability of methanol dehydrogenation was determined by probing the second-order reaction kinetics of D2 and HD formation, which is directly correlated to the surface hydrogen coverage. Under the conditions of our study, the methanol dehydrogenation probability was found to be low (∼10-3), and the lack of strong temperature dependence is consistent with dehydrogenation via a direct mechanism. Under conditions that favored methanol clustering in the incident methanol beam, the dehydrogenation probability increases significantly at low surface temperatures, which suggests a precursor-mediated mechanism. The possible role of cluster formation in enhancing the trapping probability of methanol is discussed.

Molecular polaritons, hybrid light-matter states formed from the strong coupling of molecular transitions and discrete photonic modes, are a compelling platform for optical control of chemical reactivity. Despite the origins of the field of polaritonics in atomic gases, strong coupling of molecular gases remains underexplored. The pristine, solvent-free gas-phase environment may prove ideal for gaining mechanistic understanding of molecular behavior under strong light-matter coupling. In this work, we achieve electronic strong coupling of the B-X, ν1 = 0 → 32, J = 53 → 52 and B-X, ν1 = 0 → 34, J = 103 → 102 rovibronic transitions of gas-phase iodine (I2) lying near 532.2 nm. We access a range of coupling strengths and detuning conditions with fine control over molecular number density and cavity length stabilization. This effort represents the first demonstration of electronic polaritons in a molecular gas and opens a new platform for polariton photochemistry and photophysics.

Polymer topology influences the structural and dynamic behavior of macromolecules, particularly under non-equilibrium conditions such as shear flow. As a result, conventional Gaussian chain models fail to capture the complex deformation and relaxation dynamics of polymers with branched architectures. In this study, we present a combination of Brownian dynamics simulations with Gram-Charlier (G-C) expansion analysis to quantify non-Gaussian features using two cumulant-based metrics: the standard deviation σ of the one-dimensional projected configurational distribution, where larger values indicate greater deformation, and the normalized fourth cumulant κ4/σ4, where larger values indicate stronger non-Gaussianity. Focusing on linear and star polymers in dilute solution, we systematically investigate how molecular architecture, finite extensibility, and hydrodynamic interactions (HI) influence their deformation and conformational response in shear flow. Our findings reveal that star polymers exhibit constrained global extension but enhanced local stretching near the core, resulting in reduced deviations from Gaussian behavior compared to linear chains. Finite extensibility imposes an upper limit on bond extension, which suppresses configurational deformation at high shear rates and leads to a non-monotonic trend in κ4/σ4. By contrast, hydrodynamic interactions introduce long-range segmental coupling that enhances coordinated motion and amplifies non-Gaussian character, resulting in higher values of κ4/σ4 under strong shear flow. Together, these results establish a robust framework for characterizing the influence of polymer topology on non-equilibrium conformations, offering new insights into the mechanics of branched polymer systems under flow.

Polymer crystallization is a process of great interest in both fundamental theory and industrial settings, particularly in polymer processing and applications involving semi-crystalline materials. The effect of processing on the initial stages of crystallization is not fully understood. Our study investigates the influence of pre-shear on monodisperse melts and bidisperse blends of a generic, segmentally coarse-grained polymer model. Through molecular dynamics simulations, we explore how polydispersity affects crystallization, where we found that the addition of short chains to a melt of longer chains increased the end-of-simulation crystallinity by about 10% and increased the initial growth rate by roughly a factor of two. In contrast, however, pre-shearing the hot melt before quenching only showed a minor increase in both growth rates and final crystallinity, except in monodisperse melts of short chains. Crystal grain shapes were most influenced by pre-shearing monodisperse melts, where both asphericity and prolateness decreased. In addition, we determined topological connectivity of crystal grains through tie- and loop-chain analysis. Again, only monodisperse melts showed a significant increase of tie chain fractions with pre-shear, while all other systems showed only modest increases. Our findings provide insight into the changes of crystallinity and cluster morphologies that emerge when pre-sheared, offering a deeper understanding of the initial crystallization processes in polymer melts when subjected to pre-shear.

In this work, high-level density functional theory calculations were employed to investigate the cross-linking reactions of hydrogen silsesquioxane (HSQ) radicals. We provide a comprehensive elucidation of the whole reaction process, spanning from hydroxylation of hydrogen silsesquioxane radical by water to dehydration condensation of hydroxylated HSQ molecules, by the characterization of key species, energy barriers, and reaction energies. Furthermore, the potential effect of ambient humidity on the cross-linking process was assessed by involving an extra water molecule in both the hydroxylation and dehydration condensation reaction steps. We found that the participation of an extra water molecule can reduce the transition-state energies of both reactions relative to the corresponding reactants by hydrogen-bonds. By incorporating the water concentration at a specific humidity into the kinetic calculations, we demonstrated that the extra water molecules do not catalyze the hydroxylation of HSQ radicals; however, the water molecules facilitate the dehydration condensation reaction, potentially increasing the rate constants by up to a factor of three under high-humidity conditions, as compared to the anhydrous reaction. This study provides a theoretical explanation for that the presence of water promotes HSQ cross-linking, suggesting that a sufficiently high humidity could be beneficial in practical production processes.

We present a stochastic diabatic projection method for constructing electronic structure models that operate at coarse-grained (CG) molecular resolutions. By minimizing the relative entropy of joint electronic-nuclear distributions between the fine-grained (FG) and CG resolutions, we derive a stochastic effective Hamiltonian that decomposes CG configuration dependent electronic structure into deterministic means and residual fluctuations. This framework bridges downfolding and molecular coarse-graining theory, enabling the systematic reproduction of electronic structure renormalized over eliminated nuclear and electronic degrees of freedom.

The characterization of nanostructured materials under reactive environments is challenging due to the complexity of the structural motifs involved and their chemical transformations. Global optimization approaches allow predicting stable structures for targeted materials, but addressing the configurational and compositional search spaces is both computationally demanding and inefficient, especially when first-principles calculations are required. In this work, we implement and evaluate a computationally efficient grand canonical global optimization algorithm able to identify stable structures and chemical states of targeted systems under given reaction conditions (e.g., reactant pressure and temperature). The algorithm leverages an on-the-fly trained machine-learning interatomic potential based on sparse Gaussian process regression and the smooth overlap of atomic positions descriptor to reduce the number of first-principles energy evaluations carried out during global optimization searches. The ab initio thermodynamics framework is incorporated to approximate the Gibbs energy of evaluated candidates, performing environment-aware optimizations over multiple stoichiometries. We demonstrate the computational performance of this approach and its ability to reproduce some literature examples.

We introduce a systematic hierarchy of one-body Green's function methods derived from the GW approximation, constructed by progressively reducing the dynamical content of the self-energy. Starting from the fully dynamical Dyson formulation, we generate a family of approximations that interpolates between the standard GW approximation and purely static effective single-particle Hamiltonians. This framework enables a controlled investigation of the role of dynamical effects and particle-hole coupling in the description of ionization potentials. Within this unified formalism, the hole and particle branches can be selectively decoupled through downfolding strategies into reduced one-particle spaces. By benchmarking the different members of this hierarchy on molecular ionization energies, we assess their accuracy, numerical robustness, and algorithmic complexity. We demonstrate that consistently derived partially static schemes can yield reliable quasiparticle energies while significantly simplifying the underlying eigenvalue problem. We further introduce a novel static Hermitian self-energy obtained as the static limit of this hierarchy. Despite its conceptually distinct origin, it produces results remarkably close to those of qsGW, thereby providing an alternative static route toward partial self-consistency.

Velocity slip at the solid-fluid (SF) interface plays a key role in fluid transport at the nanoscale, and the SF friction coefficient has been extensively studied because it indicates the degree of slippage. Owing to the scale of this phenomenon, molecular dynamics (MD) simulations are commonly employed using two major approaches: the Green-Kubo integral method in equilibrium MD (EMD) and the direct calculation of friction force and slip velocity in non-equilibrium MD (NEMD) systems under shear. Regarding the latter, a strict definition of the slip velocity is missing due to the nonzero thickness of the boundary at the microscale, and the average velocity of the first adsorption layer or the velocity at the boundary obtained by extrapolation or interpolation is often used. In this study, we propose an alternative description of the slip velocity based on a thermal perspective from the two different scales, i.e., at the macroscale, frictional heat is defined as the product of the friction force and slip velocity, whereas at the microscale, it can be expressed as the sum of the works exerted on the fluid and solid by each other. By combining the two different scales, we defined the slip velocity based on the dissipation induced at the SF interface under shear, which avoids the arbitrariness in the slip velocity at the microscale.

A new van der Waals potential energy surface (PES) for the NO A2Σ+ + Ne collision complex is reported. This system provides a great test for electronic structure by directly contrasting exact quantum scattering simulations on generated potential energy surfaces with the experiment. The need for a new PES for this system is apparent due to discrepancies in calculated differential cross sections for inelastic rotational scattering on older PESs compared to recent experimental data. We thus perform a detailed benchmarking of the effects of electron correlation, basis set size and type, core correlation, non-Born-Oppenheimer effects, and relativistic effects. Following this, we then construct a new PES and compare time-independent quantum scattering on this new potential to two older ones. Agreement with the experiment is improved on the new PES but still not exact at all scattering energies.

A quantum machine learning based Δ-learning framework is presented for the prediction of reaction barrier heights of organic molecules. Corrections learned by quantum kernel-based models are applied to mitigate the underlying errors of the semiempirical PM7 method, improving its predictive accuracy toward results obtained at the ωB97X-D3/def2-TZVP level of theory. Both fidelity and projected quantum kernels are implemented using seven distinct encoding circuits and passed to three classical regression algorithms, namely, support vector regression, kernel ridge regression, and Gaussian process regression, yielding a total of 840 benchmarked model configurations across circuit widths of up to 9 qubits and circuit depths of up to five layer repetitions. The encoding circuits are additionally characterized in terms of their expressibility and entangling capability. The top-performing models, constructed using the 9-qubit YZ-CX encoding circuit, predict reaction barrier heights with a mean absolute error ranging between 4.95 and 5.03 kcal/mol, underscoring an improvement of ∼54% over the uncorrected PM7 baseline.

Strong coupling with circularly polarized vacuum fluctuations offers a viable route to manipulate molecular chirality. While experiments are advancing toward the realization of chiral cavities, a mean-field theoretical framework for describing electron-photon interaction in this platform has been missing. Here, we present a mean-field theory that can be systematically improved to capture the chiral correlation effects responsible for the enantioselective power of chiral light. We use strong coupling Møller-Plesset perturbation theory for accessing the excitation manifold of electrons and chiral virtual photons. We apply the developed methods to selected chiral systems and show that the mean-field theory captures cavity frequency dispersion but fails to describe the chiral discrimination arising from coupled electron-photon excitations.