Computing inelastic neutron scattering spectra from molecular dynamics trajectories

Multiphonon scattering formula of dynamic structure factors for classical Debye solids

A semianalytic formula of the dynamic structure factor S(k,ω) for classical Debye solids over the entire wave-number (k) and frequency (ω) range is constructed by taking into account multiphonon thermal diffuse scattering up to infinite order. The formula adopts Gaussian approximations to the spatial and time decay of the multiphonon part of the displacement correlation function. Numerical illustrations for isotropic polycrystals reveal that, as k increases, sharp peaks due to one-phonon normal scattering in the hydrodynamic regime (k→0) are replaced by diffuse spectra consisting of umklapp scattering and multiphonon continuum; approach toward the ideal-gas spectra in the large-k limit is proven from analytic properties of the multiphonon term. When k coincides with a Bragg reflection point, total thermal diffuse scattering S_{TDS}(k,ω) exhibits a 1/ω divergence as ω→0, which in turn gives rise to a logarithmic enhancement of the corresponding static structure factor S_{TDS}(k). Overall accuracy of the theory is confirmed through the exact zeroth-order frequency-moment sum rule between S_{TDS}(k,ω) and S_{TDS}(k); agreement with the second-order sum rule is shown to be satisfactory except for the vicinity of the Debye cutoff region.

Neutron Scattering Studies of Heterogeneous Catalysis

Understanding the structural dynamics/evolution of catalysts and the related surface chemistry is essential for establishing structure-catalysis relationships, where spectroscopic and scattering tools play a crucial role. Among many such tools, neutron scattering, though less-known, has a unique power for investigating catalytic phenomena. Since neutrons interact with the nuclei of matter, the neutron-nucleon interaction provides unique information on light elements (mainly hydrogen), neighboring elements, and isotopes, which are complementary to X-ray and photon-based techniques. Neutron vibrational spectroscopy has been the most utilized neutron scattering approach for heterogeneous catalysis research by providing chemical information on surface/bulk species (mostly H-containing) and reaction chemistry. Neutron diffraction and quasielastic neutron scattering can also supply important information on catalyst structures and dynamics of surface species. Other neutron approaches, such as small angle neutron scattering and neutron imaging, have been much less used but still give distinctive catalytic information. This review provides a comprehensive overview of recent advances in neutron scattering investigations of heterogeneous catalysis, focusing on surface adsorbates, reaction mechanisms, and catalyst structural changes revealed by neutron spectroscopy, diffraction, quasielastic neutron scattering, and other neutron techniques. Perspectives are also provided on the challenges and future opportunities in neutron scattering studies of heterogeneous catalysis.

Computational Approaches for Organic Semiconductors: From Chemical and Physical Understanding to Predicting New Materials

While a complete understanding of organic semiconductor (OSC) design principles remains elusive, computational methods─ranging from techniques based in classical and quantum mechanics to more recent data-enabled models─can complement experimental observations and provide deep physicochemical insights into OSC structure-processing-property relationships, offering new capabilities for in silico OSC discovery and design. In this Review, we trace the evolution of these computational methods and their application to OSCs, beginning with early quantum-chemical methods to investigate resonance in benzene and building to recent machine-learning (ML) techniques and their application to ever more sophisticated OSC scientific and engineering challenges. Along the way, we highlight the limitations of the methods and how sophisticated physical and mathematical frameworks have been created to overcome those limitations. We illustrate applications of these methods to a range of specific challenges in OSCs derived from π-conjugated polymers and molecules, including predicting charge-carrier transport, modeling chain conformations and bulk morphology, estimating thermomechanical properties, and describing phonons and thermal transport, to name a few. Through these examples, we demonstrate how advances in computational methods accelerate the deployment of OSCsin wide-ranging technologies, such as organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), organic thermoelectrics, organic batteries, and organic (bio)sensors. We conclude by providing an outlook for the future development of computational techniques to discover and assess the properties of high-performing OSCs with greater accuracy.

Comparing the Expense and Accuracy of Methods to Simulate Atomic Vibrations in Rubrene

Atomic vibrations can inform about materials properties from hole transport in organic semiconductors to correlated disorder in metal-organic frameworks. Currently, there are several methods for predicting these vibrations using simulations, but the accuracy-efficiency tradeoffs have not been examined in depth. In this study, rubrene is used as a model system to predict atomic vibrational properties using six different simulation methods: density functional theory, density functional tight binding, density functional tight binding with a Chebyshev polynomial-based correction, a trained machine learning model, a pretrained machine learning model called ANI-1, and a classical forcefield model. The accuracy of each method is evaluated by comparison to the experimental inelastic neutron scattering spectrum. All methods discussed here show some accuracy across a wide energy region, though the Chebyshev-corrected tight-binding method showed the optimal combination of high accuracy with low expense. We then offer broad simulation guidelines to yield efficient, accurate results for inelastic neutron scattering spectrum prediction.

Spectroscopic Signatures of Hydrogen-Bonding Motifs in Protonic Ionic Liquid Systems: Insights from Diethylammonium Nitrate in the Solid State

Diethylammonium nitrate, [N0 0 2 2][NO3], and its perdeuterated analogue, [N D D 2 2] [NO3], were structurally characterized and studied by infrared, Raman, and inelastic neutron scattering (INS) spectroscopy. Using these experimental data along with state-of-the-art computational materials modeling, we report unambiguous spectroscopic signatures of hydrogen-bonding interactions between the two counterions. An exhaustive assignment of the spectral features observed with each technique has been provided, and a number of distinct modes related to NH···O dynamics have been identified. We put a particular emphasis on a detailed interpretation of the high-resolution, broadband INS experiments. In particular, the INS data highlight the importance of conformational degrees of freedom within the alkyl chains, a ubiquitous feature of ionic liquid (IL) systems. These findings also enable an in-depth physicochemical understanding of protonic IL systems, a first and necessary step to the tailoring of hydrogen-bonding networks in this important class of materials.