Anomalous heat transport in one-dimensional nanostructures, such as nanotubes and nanowires, is a widely debated problem in condensed matter and statistical physics, with contradicting pieces of evidence from experiments and simulations. Using a comprehensive modeling approach, comprised of lattice dynamics and molecular dynamics simulations, we proved that the infinite length limit of the thermal conductivity of a (10,0) single-wall carbon nanotube is finite but this limit is reached only for macroscopic lengths due to a thermal phonon mean free path of several millimeters. Our calculations showed that the extremely high thermal conductivity of this system at room temperature is dictated by quantum effects. Modal analysis showed that the divergent nature of thermal conductivity, observed in one-dimensional model systems, is suppressed in carbon nanotubes by anharmonic scattering channels provided by the flexural and optical modes with polarization in the plane orthogonal to the transport direction.

Anomalous heat transport in one-dimensional nanostructures, such as nanotubes and nanowires, is a widely debated problem in condensed matter and statistical physics, with contradicting pieces of evidence from experiments and simulations. Using a comprehensive modeling approach, comprised of lattice dynamics and molecular dynamics simulations, we proved that the infinite length limit of the thermal conductivity of a (10,0) single-wall carbon nanotube is finite but this limit is reached only for macroscopic lengths due to thermal phonon mean free path of several millimeters. Our calculations showed that the extremely high thermal conductivity of this system at room temperature is dictated by quantum effects. Modal analysis showed that the divergent nature of thermal conductivity, observed in one-dimensional model systems, is suppressed in carbon nanotubes by anharmonic scattering channels provided by the flexural and optical modes with polarization in the plane orthogonal to the transport direction.

Understanding heat transport in semiconductors and insulators is of fundamental importance because of its technological impact in electronics and renewable energy harvesting and conversion. Anharmonic lattice dynamics provides a powerful framework for the description of heat transport at the nanoscale. One of the advantages of this method is that it naturally includes quantum effects due to atoms vibrations, which are needed to compute the thermal properties of semiconductors widely used in nanotechnology, like silicon and carbon, even at room temperature. While the heat transport picture substantially differs between amorphous and crystalline semiconductors from a microscopic standpoint, a unified approach to simulate both crystals and glasses has been devised. Here, we introduce a unified workflow, which implements both the Boltzmann Transport equation and the quasi-harmonic Green-Kubo methods. We discuss how the theory can be optimized to exploit modern parallel architectures, and how it is implemented in κALD o: a versatile and scalable open-source software to compute phonon transport in solids. This approach is applied to crystalline and partially disordered silicon-based systems, including bulk silicon and clathrates, and on silicon-germanium alloy clathrates with largely reduced thermal conductivity.

Photochemical reactions of contaminants in snow and ice can be important sinks for organic and inorganic compounds deposited onto snow from the atmosphere and sources for photoproducts released from snowpacks into the atmosphere. Snow contaminants can be found in the bulk ice matrix, in internal liquid-like regions (LLRs), or in quasi-liquid layers (QLLs) at the air-ice interface, where they can readily exchange with the firn air. Some studies have reported that direct photochemical reactions occur faster in LLRs and QLLs than in aqueous solution, while others have found similar rates. Here, we measure the photodegradation rate constants for loss of the three dimethoxybenzene isomers under varying experimental conditions, including in aqueous solution, in LLRs, and at the air-ice interface of nature-identical snow. Relative to aqueous solution, we find modest photodegradation enhancements (3- and 6-fold) in LLRs for two of the isomers and larger enhancements (15- to 30-fold) at the air-ice interface for all three isomers. We use computational modeling to assess the impact of light absorbance changes on photodegradation rate enhancements at the interface. We find small (2-5gnm) bathochromic (red) absorbance shifts at the interface relative to in solution, which increases light absorption, but this factor only accounts for less than 50g% of the measured rate constant enhancements. The major factor responsible for photodegradation rate enhancements at the air-ice interface appears to be more efficient photodecay: estimated dimethoxybenzene quantum yields are 6- to 24-fold larger at the interface compared to in aqueous solution and account for the majority (51g%-96g%) of the observed enhancements. Using a hypothetical model compound with an assumed Gaussian-shaped absorbance peak, we find that a shift in the peak to higher or lower wavelengths can have a minor to substantial impact on photodecay rate constants, depending on the original location of the peak and the magnitude of the shift. Changes in other peak properties at the air-ice interface, such as peak width and height (i.e., molar absorption coefficient), can also impact rates of light absorption and direct photodecay. Our results suggest our current understanding of photodegradation processes underestimates the rate at which some compounds are broken down, as well as the release of photoproducts into the atmosphere.

Some organic pollutants in snowpacks undergo faster photodegradation than in solution. One possible explanation for such effect is that their UV-visible absorption spectra are shifted toward lower energy when the molecules are adsorbed at the air-ice interface. However, such bathochromic shift is difficult to measure experimentally. Here, we employ a multiscale/multimodel approach that combines classical and first-principles molecular dynamics, quantum chemical methods, and statistical learning to compute the light absorption spectra of two phenolic molecules in different solvation environments at the relevant thermodynamic conditions. Our calculations provide an accurate estimate of the bathochromic shift of the lowest-energy UV-visible absorption band when these molecules are adsorbed at the air-ice interface, and they shed light into its molecular origin.

Nanoengineered metal@zeolite materials have recently emerged as a promising class of catalysts for several industrially relevant reactions. These materials, which consist of small transition metal nanoclusters confined within three-dimensional zeolite pores, are interesting because they show higher stability and better sintering resistance under reaction conditions. While several such hybrid catalysts have been reported experimentally, key questions such as the impact of the zeolite frameworks on the properties of the metal clusters are not well understood. To address such knowledge gaps, in this study, we report a robust and transferable machine learning-based potential (MLP) that is capable of describing the structure, stability, and dynamics of zeolite-confined gold nanoclusters. Specifically, we show that the resulting MLP maintains ab initio accuracy across a range of temperatures (300-1000 K) and can be used to investigate time scales (>10 ns), length scales (ca. 10,000 atoms), and phenomena (e.g., ensemble-averaged stability and diffusivity) that are typically inaccessible using density functional theory (DFT). Taken together, this study represents an important step in enabling the rational theory-guided design of metal@zeolite catalysts.

Snowpacks contain a wide variety of inorganic and organic compounds, including some that absorb sunlight and undergo direct photoreactions. How the rates of these reactions in, and on, ice compare to rates in water is unclear: some studies report similar rates, while others find faster rates in/on ice. Further complicating our understanding, there is conflicting evidence whether chemicals react more quickly at the air-ice interface compared to in liquid-like regions (LLRs) within the ice. To address these questions, we measured the photodegradation rate of guaiacol (2-methoxyphenol) in various sample types, including in solution, in ice, and at the air-ice interface of nature-identical snow. Compared to aqueous solution, we find modest rate constant enhancements (increases of 3- to 6-fold) in ice LLRs, and much larger enhancements (of 17- to 77-fold) at the air-ice interface of nature-identical snow. Our computational modeling suggests the absorption spectrum for guaiacol red-shifts and increases on ice surfaces, leading to more light absorption, but these changes explain only a small portion (roughly 2 to 9%) of the observed rate constant enhancements in/on ice. This indicates that increases in the quantum yield are primarily responsible for the increased photoreactivity of guaiacol on ice; relative to solution, our results suggest that the quantum yield is larger by a factor of roughly 3-6 in liquid-like regions and 12-40 at the air-ice interface.

Recent development of dopant induced solubility control (DISC) patterning of polymer semiconductors has enabled direct-write optical patterning of poly-3-hexylthiophene (P3HT) with diffraction limited resolution. Here, the optical DISC patterning technique to the most simple circuit element, a wire, is applied. Optical patterning of P3HT and P3HT doped with the molecular dopant 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ) wires with dimensions of 20–70 nm thickness, 200–900 nm width, and 40 μm length is demonstrated. In addition, optical patterning of wire patterns like “L” bends and “T” junctions without changing the diameter or thickness of the wires at the junctions is demonstrated. The wires themselves show up to 0.034 S cm-1 conductance when sequentially doped. It is also demonstrated that a P3HT nanowire can be doped, de-doped, and re-doped from solution without changing the dimension of the wire. The combined abilities to optically pattern and reversibly dope a polymer semiconductor represents a full suite of patterning steps equivalent to photolithography for inorganic semiconductors.